Machines

Open AccessEditor’s ChoiceArticle

Detection for Disc Cutter Wear of TBM Using Magnetic Force

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Machines 2023, 11(3), 388; https://doi.org/10.3390/machines11030388 - 15 Mar 2023

Viewed by 568

Abstract

To replace the worn-out cutter of tunnel boring machines timely, it is crucial to inspect the cutter’s wear. In this work, a novel detection method based on magnetic force is proposed to overcome the drawback of nonlinearity in current detecting technology. The principle [...] Read more.

To replace the worn-out cutter of tunnel boring machines timely, it is crucial to inspect the cutter’s wear. In this work, a novel detection method based on magnetic force is proposed to overcome the drawback of nonlinearity in current detecting technology. The principle is that the magnetic force between the cutter and the permanent magnet linearly decreases with increasing wear. Firstly, the magnetic force is investigated by the finite element simulation to find the optimal placement of the permanent magnet to realize both high linearity and sensitivity. Secondly, a highly-sensitive force sensor with an S shape is designed to measure the magnetic force. The four strain gauges in the force sensor are combined into a Wheatstone bridge to suppress the common-mode effect, such as temperature. Experimental testing on the magnetic force is performed to verify the feasibility of the detection method. The testing result shows that the magnetic force linearly decreases with the increasing wear loss at a rate of −793 mN/mm. The accuracy of the detecting method approaches 1 mm, which is of the same order of magnitude as those in previous studies. Full article

(This article belongs to the Special Issue Tool Wear in Machining)

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Open AccessEditor’s ChoiceArticle

Modeling and Analysis of a Novel 3R Parallel Compliant Mechanism

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Machines 2023, 11(3), 375; https://doi.org/10.3390/machines11030375 - 10 Mar 2023

Viewed by 587

Abstract

This paper presents and investigates a new three-rotation (3R) parallel compliant mechanism that uses compliant rods to achieve three rotations. The mechanism is designed for use in pointing devices or as a spatial parallel manipulator. The mobility analysis is based on the Cosserat [...] Read more.

This paper presents and investigates a new three-rotation (3R) parallel compliant mechanism that uses compliant rods to achieve three rotations. The mechanism is designed for use in pointing devices or as a spatial parallel manipulator. The mobility analysis is based on the Cosserat rod model and Lagrangian dynamics equations. The dynamics equations are then effectively solved using the back-propagation neural network and chaos-enhanced accelerated particle swarm optimization. After studying the mobility of the moving platform, a simplified model is proposed and used for kinematic analysis. The analysis of motion includes discussions on forward kinematics, inverse kinematics, singularities, and the workspace. Furthermore, experiments with a prototype are conducted to verify the accuracy and stability of the mobility analysis and the simplified model. Full article

(This article belongs to the Section Automation and Control Systems)

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Open AccessEditor’s ChoiceArticle

Frame Angular Velocity Control Design of SGCMG for Unmanned Two-Wheeled Motorcycle

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Machines 2023, 11(3), 371; https://doi.org/10.3390/machines11030371 - 09 Mar 2023

Viewed by 566

Abstract

In contrast to driverless cars and other three-wheeled and four-wheeled motorcycle vehicles, driverless two-wheeled motorcycles have the problem of maintaining balance. In this paper, we propose the design of an SGCMG frame angular velocity controller to realize the balance control of the motorcycle [...] Read more.

In contrast to driverless cars and other three-wheeled and four-wheeled motorcycle vehicles, driverless two-wheeled motorcycles have the problem of maintaining balance. In this paper, we propose the design of an SGCMG frame angular velocity controller to realize the balance control of the motorcycle under static and dynamic working conditions. Meanwhile, since the roll angular acceleration of the actual body movement of the cross roll cannot be obtained directly, this paper proposes a Kalman filtering method based on the nonlinear dynamics model of the motorcycle to obtain a reliable angular acceleration signal. First, we modeled the dynamics of the motorcycle by analyzing the various types of moments generated by the motorcycle equipped with the SGCMG under static and dynamic conditions; Then, the design of the angular velocity control of the SGCMG frame was carried out with the feedback and through MATLAB/Simulink simulation to restore various types of actual working conditions to verify the controller has good robustness; Finally, we have completed the test of the controller using the above filtering method on the real vehicle with an embedded system and compared the effect with other controllers, obtained the results that the body is stable and balanced under static conditions and the applied load can automatically find a new balance point, so as to prove the effectiveness of the designed control. Full article

(This article belongs to the Special Issue Noise and Vibration Control in Dynamic Systems)

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Open AccessEditor’s ChoiceArticle

Design and Verification of Adaptive Adjustable Output Control on Micro Spray Gun

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Jiun-Hung Lin

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Chih-Hong Chen

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Shih-Tsang Tang

Machines 2023, 11(3), 354; https://doi.org/10.3390/machines11030354 - 04 Mar 2023

Viewed by 572

Abstract

The general spray gun is used for industrial large-area spraying, and there is less demand for different pressures and the accuracy of spraying pressure, so mechanical pressure regulators are mostly used. However, as the demand for artistic innovation continues to grow, it promotes [...] Read more.

The general spray gun is used for industrial large-area spraying, and there is less demand for different pressures and the accuracy of spraying pressure, so mechanical pressure regulators are mostly used. However, as the demand for artistic innovation continues to grow, it promotes the advent of the micro spray gun. The micro spray gun is currently commonly known as an airbrush. The micro spray gun is mainly used for fine drawing, so it must provide different pressures with high precision pressures, but the existing mechanical regulators cannot meet this requirement. For these unmet requirements, this study proposed a solution for PID (proportional-integral-derivative) control micro spray gun system. The results showed that the PID control could effectively provide various stable output pressures of the micro spray gun. The pressure-varying range of 30 kPa could rapidly return to the target value in 10 s (the usual spraying time). The proposed solution then presents better spraying effects. Full article

(This article belongs to the Topic Designs and Drive Control of Electromechanical Machines)

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Open AccessEditor’s ChoiceArticle

Robust Control of UAV with Disturbances and Uncertainty Estimation

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Domenico Bianchi

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Stefano Di Gennaro

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Mario Di Ferdinando

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Cuauhtémoc Acosta Lùa

Machines 2023, 11(3), 352; https://doi.org/10.3390/machines11030352 - 03 Mar 2023

Viewed by 573

Abstract

In this work, a nonlinear estimator-based robust controller is designed for the position and yaw control of a quadrotor with uncertainty estimation. This controller ensures the tracking of desired references in the presence of parameters variation and external disturbances, making use of high-order [...] Read more.

In this work, a nonlinear estimator-based robust controller is designed for the position and yaw control of a quadrotor with uncertainty estimation. This controller ensures the tracking of desired references in the presence of parameters variation and external disturbances, making use of high-order sliding mode (HOSM) estimators to estimate these perturbations that can be canceled by the control, thus improving the dynamic behavior of the controlled system. Its performance is evaluated making use of a Simcenter Amesim quadrotor based on physical models generated from experimental data in a co-simulation framework with Matlab–Simulink used to implement the designed controller with FPGA implementation. A challenging and generic maneuver with time-varying wind disturbances and uncertainty model parameters is considered. Full article

(This article belongs to the Special Issue Robust Control of Robotic and Complex Mechatronic Systems)

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Open AccessEditor’s ChoiceArticle

Nonlinear Dynamic Characteristics of Deep Groove Ball Bearings with an Improved Contact Model

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Machines 2023, 11(3), 340; https://doi.org/10.3390/machines11030340 - 01 Mar 2023

Cited by 1 | Viewed by 602

Abstract

In this paper, the nonlinear dynamic response of deep groove ball bearings with clearance was studied numerically. The imperfect connections with the clearance of raceways and rolling balls were established by the contact elements. In order to describe the contact characteristics accurately, a [...] Read more.

In this paper, the nonlinear dynamic response of deep groove ball bearings with clearance was studied numerically. The imperfect connections with the clearance of raceways and rolling balls were established by the contact elements. In order to describe the contact characteristics accurately, a hysteresis damping coefficient was introduced into the Hertz contact model, which represented the dissipative term during the contact–impact process. The tangential force of the contact bodies was obtained based on a modified Coulomb friction model. Then, the dynamic analysis model of the deep groove ball bearings with clearance was built. Meanwhile, the experimental test platform of the deep groove ball bearings with various operation conditions was built and the dynamic simulation was utilized as the demonstrative case to conduct the investigation. The numerical results revealed that the existence of clearance would change the motion trajectory of a rolling ball and the appearance of the different movement states (free, contact, and penetration). In addition, the contact characteristics and sliding features would be changed with the variations in the operation conditions and structural characteristics. Full article

(This article belongs to the Special Issue Friction and Lubrication of Mechanical Drive Train Components)

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Open AccessEditor’s ChoiceArticle

Minimum Dynamic Cable Tension Workspace Generation Techniques and Cable Tension Sensitivity Analysis Methods for Cable-Suspended Gangue-Sorting Robots

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Machines 2023, 11(3), 338; https://doi.org/10.3390/machines11030338 - 01 Mar 2023

Cited by 1 | Viewed by 452

Abstract

The separation of gangues from coals with robots is an effective and practicable means. Therefore, a cable-suspended gangue-sorting robot (CSGSR) with an end-grab was developed in our early work. Due to the unidirectional characteristic, the flexibility of cables, and the dynamic impact of [...] Read more.

The separation of gangues from coals with robots is an effective and practicable means. Therefore, a cable-suspended gangue-sorting robot (CSGSR) with an end-grab was developed in our early work. Due to the unidirectional characteristic, the flexibility of cables, and the dynamic impact of pick-and-place gangues, one of the significant issues with the robots is robustness under internal and external disturbances. Cable tensions, being the end-grab’s constraints, have a crucial effect on the robustness of the CSGSR while disturbances are on. Two main issues related to the CSGSR, as a result, are addressed in the present paper: minimum dynamic cable tension workspace generation and a sensitivity analysis method for the dynamic cable tensions. Firstly, the four cable tensions and minimum dynamic cable tension while the end-grab was located at an arbitrary position of the task space were obtained with the dynamics of the CSGSR. In addition, with the dynamics of the CSGSR, a minimum dynamic cable tension workspace (MDCTW) generating approach is presented, where the minimum dynamic cable tensions are greater than a preset value, therefore ensuring the robustness of the end-grab under the disturbances. Secondly, a method for dynamic cable tension sensitivity (DCTS) of the robots is proposed with grey relational analysis, by which the influence degree of the end-grab’s positions on the four dynamic cable tensions and the minimum dynamic cable tensions was considered. Finally, the effectiveness of the proposed MDCTW generation algorithm and the DCTS analysis method were examined through simulation on the CSGSR, and it was indicated that the proposed MDCTW generation algorithm and the DCTS analysis method were able to provide theoretical guidance for pick-and-place trajectory planning and generation of the end-grab in practice. Full article

(This article belongs to the Special Issue Development and Applications of Parallel Robots)

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Open AccessEditor’s ChoiceReview

Review on Wearable System for Positioning Ultrasound Scanner

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Machines 2023, 11(3), 325; https://doi.org/10.3390/machines11030325 - 24 Feb 2023

Viewed by 1515

Abstract

Although ultrasound (US) scan or diagnosis became widely employed in the 20th century, it still plays a crucial part in modern medical diagnostics, serving as a diagnostic tool or a therapy process guide. This review provides information on current wearable technologies and applications [...] Read more.

Although ultrasound (US) scan or diagnosis became widely employed in the 20th century, it still plays a crucial part in modern medical diagnostics, serving as a diagnostic tool or a therapy process guide. This review provides information on current wearable technologies and applications used in external ultrasound scanning. It offers thorough explanations that could help build upon any project utilizing wearable external US devices. It touches on several aspects of US scanning and reviews basic medical procedure concepts. The paper starts with a detailed overview of ultrasound principles, including the propagation speed of sound waves, sound wave interactions, image resolution, transducers, and probe positioning. After that, it explores wearable external US mounts and wearable external US transducers applied for sonograph purposes. The subsequent section tackles artificial intelligence methods in wearable US scanners. Finally, future external US scan directions are reported, focusing on hardware and software. Full article

(This article belongs to the Section Automation and Control Systems)

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Open AccessEditor’s ChoiceArticle

Semi-Active Vibration Control of Seat Suspension Equipped with a Variable Equivalent Inertance-Variable Damping Device

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Machines 2023, 11(2), 284; https://doi.org/10.3390/machines11020284 - 14 Feb 2023

Viewed by 861

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The seat suspension has a significant influence on riding comfort in many practical applications, such as heavy duty vehicles, military vehicles, and high-speed crafts. This paper proposes a seat suspension equipped with a variable equivalent inertance-variable damping (VEI–VD) device and a novel semi-active [...] Read more.

The seat suspension has a significant influence on riding comfort in many practical applications, such as heavy duty vehicles, military vehicles, and high-speed crafts. This paper proposes a seat suspension equipped with a variable equivalent inertance-variable damping (VEI–VD) device and a novel semi-active vibration control strategy. The VEI–VD device can control its equivalent inertance and damping by controlling two external resistors in its electric circuit. Especially, the VEI part of the device can store and release vibration energy via the inside flywheel, which enables the seat suspension to have a four-quadrant controllable capability in the available force–velocity diagram, similar to an active system. First, the dynamic model of the VEI–VD device is built, and a prototype is developed and tested to identify the model parameters and verify its characteristics. Then, a semi-active vibration control method is proposed for the VEI–VD seat suspension. The control method uses a sliding mode controller to acquire the desired control force for reducing vibration; then, according to the desired force and system states, the VEI–VD device is tuned by a force-tracking scheme to generate a real force. In the numerical validation, the vibration transmissibility of VEI–VD seat suspension around its natural frequency is tested with different states. The effectiveness of force-tracking control strategies for different types of suspensions is verified. In the random excitation test, the root means square acceleration of the VEI–VD seat is reduced by 30.72% compared with a passive seat. The VEI–VD seat suspension shows great potential in applications. Full article

(This article belongs to the Special Issue Low-Frequency Vibration Control with Advanced Technologies)

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Open AccessEditor’s ChoiceArticle

Vision-Based Robotic Object Grasping—A Deep Reinforcement Learning Approach

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Ya-Ling Chen

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Yan-Rou Cai

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Ming-Yang Cheng

Machines 2023, 11(2), 275; https://doi.org/10.3390/machines11020275 - 12 Feb 2023

Viewed by 964

Abstract

This paper focuses on developing a robotic object grasping approach that possesses the ability of self-learning, is suitable for small-volume large variety production, and has a high success rate in object grasping/pick-and-place tasks. The proposed approach consists of a computer vision-based object detection [...] Read more.

This paper focuses on developing a robotic object grasping approach that possesses the ability of self-learning, is suitable for small-volume large variety production, and has a high success rate in object grasping/pick-and-place tasks. The proposed approach consists of a computer vision-based object detection algorithm and a deep reinforcement learning algorithm with self-learning capability. In particular, the You Only Look Once (YOLO) algorithm is employed to detect and classify all objects of interest within the field of view of a camera. Based on the detection/localization and classification results provided by YOLO, the Soft Actor-Critic deep reinforcement learning algorithm is employed to provide a desired grasp pose for the robot manipulator (i.e., learning agent) to perform object grasping. In order to speed up the training process and reduce the cost of training data collection, this paper employs the Sim-to-Real technique so as to reduce the likelihood of damaging the robot manipulator due to improper actions during the training process. The V-REP platform is used to construct a simulation environment for training the deep reinforcement learning neural network. Several experiments have been conducted and experimental results indicate that the 6-DOF industrial manipulator successfully performs object grasping with the proposed approach, even for the case of previously unseen objects. Full article

(This article belongs to the Special Issue Recent Trends and Interdisciplinary Applications of AI & Robotics)

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Open AccessEditor’s ChoiceArticle

Hard Milling Process Based on Compressed Cold Air-Cooling Using Vortex Tube for Sustainable and Smart Manufacturing

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Machines 2023, 11(2), 264; https://doi.org/10.3390/machines11020264 - 10 Feb 2023

Viewed by 784

Abstract

Improving machining performance and meeting the requirements of sustainable production at the same time represents a major challenge for the metalworking industry and scientific community. One approach to satisfying the above challenge is to apply different types of cutting fluids or to optimise [...] Read more.

Improving machining performance and meeting the requirements of sustainable production at the same time represents a major challenge for the metalworking industry and scientific community. One approach to satisfying the above challenge is to apply different types of cutting fluids or to optimise their usage during the machining process. The fact that cutting fluids are well known as significant environmental pollutants in the metalworking industry has encouraged researchers to discover new environmentally friendly ways of cooling and lubricating in the machining process. Therefore, the main goal is to investigate the influence of different machining conditions on the efficiency of hard machining and find a sustainable solution towards smart manufacturing. In the experimental part of the work, the influence of various machining parameters and conditions on the efficiency of the process was investigated and measured through the surface roughness, tool wear and cutting force components. Statistical data processing was carried out, and predictive mathematical models were developed. An important achievement is the knowledge of the efficiency of compressed cold air cooling for hard milling with the resulting lowest average flank wear of 0.05 mm, average surface roughness of 0.28 µm, which corresponds to grinding procedure roughness classes of N4 and N5, and average tool durability increase of 26% compared to dry cutting and conventional use of cutting fluids. Becoming a smart machining system was assured via technological improvement achieved through the reliable prediction of tool wear obtained by radial basis neural networks modelling, with a relative prediction error of 3.97%. Full article

(This article belongs to the Special Issue Advances in Smart Manufacturing and Industry 4.0)

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Open AccessEditor’s ChoiceArticle

Fault Diagnosis of Rotating Machinery Based on Two-Stage Compressed Sensing

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Machines 2023, 11(2), 242; https://doi.org/10.3390/machines11020242 - 06 Feb 2023

Cited by 1 | Viewed by 625

Abstract

Intelligent on-site fault diagnosis and professional vibration analysis are essential for the safety and stability of rotating machinery operation. This paper represents a fault diagnosis scheme based on two-stage compressed sensing for triaxial vibration data, which realizes fault diagnosis for rotating machinery based [...] Read more.

Intelligent on-site fault diagnosis and professional vibration analysis are essential for the safety and stability of rotating machinery operation. This paper represents a fault diagnosis scheme based on two-stage compressed sensing for triaxial vibration data, which realizes fault diagnosis for rotating machinery based on compressed data and data reconstruction for professional vibration analysis. In the 1st stage, the triaxial vibration signals are compressed using a pre-designed hybrid measurement matrix; these compressed data can be used both for time-frequency transform and for vibration data reconstruction. In the 2nd stage, the frequency spectra of the triaxial vibration signals are fused and further compressed using another pre-designed joint measurement matrix, which inhibits the high-frequency noises simultaneously. Finally, the fused spectra are employed as feature vectors in sparse-representation-based classification, where the proposed batch matching pursuit (BMP) algorithm is utilized to calculate the sparse vectors. The two-stage compression scheme and the BMP algorithm minimize the computational cost of on-site fault diagnosis, which is suitable for edge computing platforms. Meanwhile, the compressed vibration data can be reconstructed, which provides evidence for professional vibration analysis. The method proposed in this study is validated by two practical case studies, in which the accuracies are 99.73% and 96.70%, respectively. Full article

(This article belongs to the Special Issue Fault Detection, Diagnosis and Prognostics of Machines: Applications and Advances)

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Open AccessEditor’s ChoiceArticle

Shock Absorption for Legged Locomotion through Magnetorheological Leg-Stiffness Control

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Matthew Daniel Christie

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Machines 2023, 11(2), 236; https://doi.org/10.3390/machines11020236 - 06 Feb 2023

Viewed by 627

Abstract

The objective of this study was to evaluate the performance of a magnetorheological-fluid-based variable stiffness actuator leg under high impact forces through optimal tuning and control of stiffness and damping properties. To achieve this, drop testing experiments were conducted with the leg at [...] Read more.

The objective of this study was to evaluate the performance of a magnetorheological-fluid-based variable stiffness actuator leg under high impact forces through optimal tuning and control of stiffness and damping properties. To achieve this, drop testing experiments were conducted with the leg at various drop heights and payload masses. The results showed that while lower stiffness and higher damping can lead to lower impact forces and greater energy dissipation, respectively, optimal control can also protect the leg from deflecting beyond its functional range. Comparison with a rigid leg with higher damping showed a 57.5% reduction in impact force, while a more compliant leg with lower damping results in a 61.4% reduction. These findings demonstrate the importance of considering both stiffness and damping in the design of legged robots for high impact force resistance. This simultaneously highlights the efficacy of the proposed magnetorheological-fluid-based leg design for this purpose. Full article

(This article belongs to the Special Issue Low-Frequency Vibration Control with Advanced Technologies)

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Open AccessEditor’s ChoiceArticle

A Refined Dynamic Model for the Planetary Gear Set Considering the Time-Varying Nonlinear Support Stiffness of Ball Bearing

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Machines 2023, 11(2), 206; https://doi.org/10.3390/machines11020206 - 01 Feb 2023

Viewed by 589

Abstract

Dynamics models of planetary gear sets (PGSs) are usually established to predict their dynamic behavior and load-sharing characteristics. The accurate modeling of bearing support stiffness is essential to study their dynamics. However, in most of the existing PGS dynamic models, the effect of [...] Read more.

Dynamics models of planetary gear sets (PGSs) are usually established to predict their dynamic behavior and load-sharing characteristics. The accurate modeling of bearing support stiffness is essential to study their dynamics. However, in most of the existing PGS dynamic models, the effect of characteristics coupling the rolling bearing time-varying nonlinear stiffness with the translational property of PGSs on the dynamic responses was completely neglected. To investigate this problem, a refined dynamic model for PGSs is proposed considering the coupled relationship between the radial translation of the rotating components and the time-varying nonlinear support stiffness of the ball bearing. The refined dynamic model simultaneously considers the coupled effect of the time-varying characteristic caused by the orbital motion of the rolling elements and the nonlinear characteristic caused by Hertzian contact between the rolling elements and raceways of the ball bearing. Comparisons between the simulations and experimental results are presented, which indicate that the PGS vibration spectrums yielded by the proposed time-varying nonlinear stiffness model are much closer to the actual scenarios than those of traditional models. The analysis results provide theoretical guidance for fault monitoring and diagnosis of the rolling bearings used in the PGS. Full article

(This article belongs to the Special Issue Safety of Machinery: Design, Monitoring, Manufacturing)

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Open AccessEditor’s ChoiceArticle

Sound-Based Intelligent Detection of FOD in the Final Assembly of Rocket Tanks

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Machines 2023, 11(2), 187; https://doi.org/10.3390/machines11020187 - 31 Jan 2023

Viewed by 740

Abstract

The traditional method of relying on human hearing to detect foreign object debris (FOD) events during rocket tank assembly processes has the limitation of strong reliance on humans and difficulty in establishing objective detection records. This can lead to undetected FOD entering the [...] Read more.

The traditional method of relying on human hearing to detect foreign object debris (FOD) events during rocket tank assembly processes has the limitation of strong reliance on humans and difficulty in establishing objective detection records. This can lead to undetected FOD entering the engine with the fuel and causing major launch accidents. In this study, we developed an automatic, intelligent FOD detection system for rocket tanks based on sound signals to overcome the drawbacks of manual detection, enabling us to take action to prevent accidents in advance. First, we used log-Mel transformation to reduce the high sampling rate of the sound signal. Furthermore, we proposed a multiscale convolution and temporal convolutional network (MS-CTCN) to overcome the challenges of multi-scale temporal feature extraction to detect suspicious FOD events. Finally, we used the proposed post-processing strategies of label smoothing and threshold discrimination to refine the results of FOD event detection and ultimately determine the presence of FOD. The proposed method was validated through FOD experiments. The results showed that the method had an accuracy rate of 99.16% in detecting FOD and had a better potential to prevent accidents compared to the baseline method. Full article

(This article belongs to the Special Issue Intelligent Maintenance and Health Management of Electromechanical Equipment)

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Open AccessEditor’s ChoiceArticle

Explainable Data-Driven Method Combined with Bayesian Filtering for Remaining Useful Lifetime Prediction of Aircraft Engines Using NASA CMAPSS Datasets

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Faisal Maulana

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Andrew Starr

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Agusmian Partogi Ompusunggu

Machines 2023, 11(2), 163; https://doi.org/10.3390/machines11020163 - 24 Jan 2023

Viewed by 948

Abstract

An aircraft engine is expected to have a high-reliability system as a safety-critical asset. A scheduled maintenance strategy based on statistical calculation has been employed as the current practice to achieve the reliability requirement. Any improvement to this maintenance interval is made after [...] Read more.

An aircraft engine is expected to have a high-reliability system as a safety-critical asset. A scheduled maintenance strategy based on statistical calculation has been employed as the current practice to achieve the reliability requirement. Any improvement to this maintenance interval is made after significant reliability issues arise (such as flight delays and high component removals). Several publications and research studies have been conducted related to this issue, one of them involves performing simulations and providing aircraft operation datasets. The recently published NASA CMAPPS datasets have been utilised in this paper since they simulate flight data recording from various measurements. A prognostics model can be developed by analysing these datasets and predicting the engine’s reliability before failure. However, the state-of-the-art prognostics techniques published in the literature using these NASA CMAPPS datasets are mainly purely data-driven. These techniques mainly deal with a “black box” process which does not include uncertainty quantification (UQ). These two factors are barriers to prognostics applications, particularly in the aviation industry. To tackle these issues, this paper aims at developing explainable and transparent algorithms and a software tool to compute the engine health, estimate engine end of life (EoL), and eventually predict its remaining useful life (RUL). The proposed algorithms use hybrid metrics for feature selection, employ logistic regression for health index estimation, and unscented Kalman filter (UKF) to update the prognostics model for predicting the RUL in a recursive fashion. Among the available datasets, dataset 02 is chosen because it has been widely used and is an ideal candidate for result comparison and dataset 03 is employed as a new state-of-the-art. As a result, the proposed algorithms yield 34.5–55.6% better performance in terms of the root mean squared error (RMSE) compared with the previous work. More importantly, the proposed method is transparent and it quantifies the uncertainty during the prediction process. Full article

(This article belongs to the Special Issue Fault Detection, Diagnosis and Prognostics of Machines: Applications and Advances)

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Open AccessEditor’s ChoiceArticle

A Method of Improving the Length Measurement Accuracy of Metal Parts Using Polarization Vision

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Machines 2023, 11(2), 145; https://doi.org/10.3390/machines11020145 - 20 Jan 2023

Viewed by 644

Abstract

Measurement technology based on machine vision has been widely used in various industries. The development of vision measurement technology mainly depends on the process of photosensitive components and the algorithm of processing a target image. In the high-precision dimension measurement of machined metal [...] Read more.

Measurement technology based on machine vision has been widely used in various industries. The development of vision measurement technology mainly depends on the process of photosensitive components and the algorithm of processing a target image. In the high-precision dimension measurement of machined metal parts, the high-resolution imaging device usually exposes the cutting texture of the metal surface and affects the accuracy of measurement algorithm. At the same time, the edges of machined metal parts are often chamfered, which makes the edges of objects in the picture overexposed in the lighting measurement environment. These factors reduce the accuracy of dimensioning metal parts using visual measurements. The traditional vision measurement method based on color/gray image makes it difficult to analyze the physical quantities in the light field except for the light intensity, which limits the measurement accuracy. Polarization information can more carefully depict the edge contour edge information in the scene and increase the contrast between the foreground and the background. This paper presents a method to improve the measurement accuracy of machined metal parts by using polarization vision. The incident angle of the light source is optimized according to the complex refractive index of the metal material, and the degree of polarization image with enhanced edge contour features of the ROI (region of interest) is obtained. The high-precision measurement of cylindrical brass motor components is realized by using the method of reprojection transformation correction and maximum correlation template matching (NCC) for rough positioning, as well as the method of edge extraction and optimal fitting. The experimental results show that for copper parts with a tolerance range of

\pm 0.1

mm, the average measurement error and maximum measurement error are within

0.01

mm, which are higher than the existing color/gray image measurement methods. Full article

(This article belongs to the Section Machines Testing and Maintenance)

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Open AccessEditor’s ChoiceArticle

Simulation and Field Studies on an Innovative Downhole Machine Designed for Ultrashort-Radius Horizontal Well Drilling Engineering

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Machines 2023, 11(2), 139; https://doi.org/10.3390/machines11020139 - 19 Jan 2023

Viewed by 516

Abstract

Ultrashort-Radius Horizontal Well (URHW) drilling engineering plays an important role in increasing the recovery factor of old oilfields. By sidetracking old wellbores at a very high build-up rate, the URHW can effectively exploit the residual oil near old wellbores. Currently, the main problem [...] Read more.

Ultrashort-Radius Horizontal Well (URHW) drilling engineering plays an important role in increasing the recovery factor of old oilfields. By sidetracking old wellbores at a very high build-up rate, the URHW can effectively exploit the residual oil near old wellbores. Currently, the main problem faced in URHW drilling engineering is the reduced torque received by drill bits owing to the increased friction between the flexible drilling assembly and wellbore as the horizontal section extends, which greatly limits oil production from a single trip. To tackle this problem, we proposed an innovative machine design, a Dynamic Flexible Drill Rod (DFDR), to provide extra torque near the drill bit to extend the horizontal section of the URHW. The interior structure and working principle of the DFDR were illustrated. The mechanical properties of the DFDRs critical load-bearing part were examined via simulation. The torque and pressure loss characteristics were analyzed using computational fluid dynamics. Corresponding modifications were made to optimize the design, with model machines produced accordingly. Field trials were carried out based on old wellbores in Chunliang District, Shengli Oilfield. The DFDR-based technique extended the URHWs horizontal section in this area by 13.38% on average. Full article

(This article belongs to the Special Issue Machine Science and Research in Jiangsu University: Celebrating the 60th Anniversary of the Research Center of Fluid Machinery Engineering and Technology)

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Open AccessEditor’s ChoiceArticle

Fixed-Time Sliding Mode-Based Active Disturbance Rejection Tracking Control Method for Robot Manipulators

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Machines 2023, 11(2), 140; https://doi.org/10.3390/machines11020140 - 19 Jan 2023

Cited by 1 | Viewed by 574

Abstract

This work investigates the issue of a hybrid trajectory tracking control algorithm (HTCA) for robot manipulators (RMs) with uncertain dynamics and the effect of external disturbances. Following are some proposals for achieving the control target. Firstly, to achieve the active disturbance rejection, we [...] Read more.

This work investigates the issue of a hybrid trajectory tracking control algorithm (HTCA) for robot manipulators (RMs) with uncertain dynamics and the effect of external disturbances. Following are some proposals for achieving the control target. Firstly, to achieve the active disturbance rejection, we propose a uniform second-order sliding mode disturbance observer (USOSMDO) to obtain directly the lumped uncertainties without their prior upper-bound information. Secondly, a fixed-time singularity-free terminal sliding surface (FxSTSS) is proposed to obtain a fixed-time convergence of the tracking control error (TCE) without the singularity in the control input. Then, using information on the proposed USOSMDO, our HTCA is formed based on the FxSTSS and the fixed-time power rate reaching law (FxPRRL). The control proposal not only stabilizes with the global fixed-time convergence but also attains high tracking accuracy. In addition, the chattering problem also is handled almost completely. Finally, numerical simulations verify the effectiveness and advantages of applying the proposed HTCA to a FARA robot. Full article

(This article belongs to the Special Issue Motion Planning and Advanced Control for Robotics)

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Open AccessEditor’s ChoiceArticle

Unknown Slope-Oriented Research on Model Predictive Control for Quadruped Robot

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Machines 2023, 11(2), 133; https://doi.org/10.3390/machines11020133 - 18 Jan 2023

Viewed by 781

Abstract

There are many undulating terrains in the wild environment. In order to realize the adaptive and stable walking of quadruped robots on unknown sloped terrain, a slope-adaptability model predictive control (SAMPC) algorithm is proposed in this work. In the absence of external vision [...] Read more.

There are many undulating terrains in the wild environment. In order to realize the adaptive and stable walking of quadruped robots on unknown sloped terrain, a slope-adaptability model predictive control (SAMPC) algorithm is proposed in this work. In the absence of external vision sensors, the orientation and inclination of the slope are estimated based on the joint position sensors and inertial measurement units (IMU). In an effort to increase the stability margin, the adaptive algorithm adjusts the attitude angle and the touch-down point of the swing leg. To reduce the slipping risk, a nonlinear control law is designed to determine the friction factor of the friction cone constraint from the inclination of the slope. We validate the effectiveness of the framework through a series of simulations. The automatic smooth transition from the flat to the unknown slope is achieved, and the robot is capable of walking in all directions on the slope. Notably, with reference to the climbing modal of blue sheep, the robot successfully climbed a 42.4° slope, proving the ultimate ability of the proposed framework. Full article

(This article belongs to the Special Issue Motion Planning and Advanced Control for Robotics)

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Open AccessEditor’s ChoiceArticle

Numerical Investigation on the Combustion and Emission Characteristics of Diesel Engine with Flexible Fuel Injection

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Machines 2023, 11(1), 120; https://doi.org/10.3390/machines11010120 - 16 Jan 2023

Cited by 1 | Viewed by 988

Abstract

As the main engineering power plant, diesel engines are irreplaceable in the future. However, the stringent emission regulations impose many tough requirements to their developments. Recently, flexible fuel injection strategy has been recognized as an effective technology in creating an advanced spray and [...] Read more.

As the main engineering power plant, diesel engines are irreplaceable in the future. However, the stringent emission regulations impose many tough requirements to their developments. Recently, flexible fuel injection strategy has been recognized as an effective technology in creating an advanced spray and mixture formation and improving combustion efficiency indirectly. However, the detailed combustion and emission behaviors under flexible fuel injection are still unknown. Therefore, this paper aims to investigate the combustion and emission characteristics under flexible fuel injection and explore an optimal injection strategy for high-efficiency combustion. A numerical simulation method is conducted by coupling the large-eddy simulation (LES) model and the SAGE combustion model. Then, the spray mixing, combustion flame propagation and emissions formation under various multiple-injection strategies are investigated. Results reveal that initial an ultrahigh injection pressure has a significant influence on the spray’s axial penetration while dwell time mainly affects the spray’s radial expansion. Under an initial ultrahigh injection pressure, the turbulence kinetic energy (TKE) becomes larger, and the vortex motions are stronger, contributing to a better spray turbulent mixing. Meanwhile, a snatchier flame structure with a favorable level of equivalence ratio and a homogeneous temperature distribution is obtained. In this way, the peak heat release rate (HRR) could increase by 46.7% with a 16.7% reduction in soot formation and a 31.4% reduction in NO_x formation. Full article

(This article belongs to the Special Issue Advances in Combustion Science for Future IC Engines)

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Open AccessEditor’s ChoiceArticle

Fault Location in Distribution Network by Solving the Optimization Problem Based on Power System Status Estimation Using the PMU

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Masoud Dashtdar

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Arif Hussain

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Hassan Z. Al Garni

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Abdullahi Abubakar Mas’ud

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Waseem Haider

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Kareem M. AboRas

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Hossam Kotb

Machines 2023, 11(1), 109; https://doi.org/10.3390/machines11010109 - 13 Jan 2023

Cited by 3 | Viewed by 1190

Abstract

Fault location is one of the main challenges in the distribution network due to its expanse and complexity. Today, with the advent of phasor measurement units (PMU), various techniques for fault location using these devices have been proposed. In this research, distribution network [...] Read more.

Fault location is one of the main challenges in the distribution network due to its expanse and complexity. Today, with the advent of phasor measurement units (PMU), various techniques for fault location using these devices have been proposed. In this research, distribution network fault location is defined as an optimization problem, and the network fault location is determined by solving it. This is done by combining PMU data before and after the fault with the power system status estimation (PSSE) problem. Two new objective functions are designed to identify the faulty section and fault location based on calculating the voltage difference between the two ends of the grid lines. In the proposed algorithm, the purpose of combining the PMU in the PSSE problem is to estimate the voltage and current quantities at the branch point and the total network nodes after the fault occurs. Branch point quantities are calculated using the PMU and the governing equations of the π line model for each network section, and the faulty section is identified based on a comparison of the resulting values. The advantages of the proposed algorithm include simplicity, step-by-step implementation, efficiency in conditions of different branch specifications, application for various types of faults including short-circuit and series, and its optimal accuracy compared to other methods. Finally, the proposed algorithm has been implemented on the IEEE 123-node distribution feeder and its performance has been evaluated for changes in various factors including fault resistance, type of fault, angle of occurrence of a fault, uncertainty in loading states, and PMU measurement error. The results show the appropriate accuracy of the proposed algorithm showing that it was able to determine the location of the fault with a maximum error of 1.21% at a maximum time of 23.87 s. Full article

(This article belongs to the Section Energy and Power Engineering)

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Open AccessEditor’s ChoiceArticle

Path Planning of Unmanned Aerial Vehicle in Complex Environments Based on State-Detection Twin Delayed Deep Deterministic Policy Gradient

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Machines 2023, 11(1), 108; https://doi.org/10.3390/machines11010108 - 13 Jan 2023

Viewed by 1032

Abstract

This paper investigates the path planning problem of an unmanned aerial vehicle (UAV) for completing a raid mission through ultra-low altitude flight in complex environments. The UAV needs to avoid radar detection areas, low-altitude static obstacles, and low-altitude dynamic obstacles during the flight [...] Read more.

This paper investigates the path planning problem of an unmanned aerial vehicle (UAV) for completing a raid mission through ultra-low altitude flight in complex environments. The UAV needs to avoid radar detection areas, low-altitude static obstacles, and low-altitude dynamic obstacles during the flight process. Due to the uncertainty of low-altitude dynamic obstacle movement, this can slow down the convergence of existing algorithm models and also reduce the mission success rate of UAVs. In order to solve this problem, this paper designs a state detection method to encode the environmental state of the UAV’s direction of travel and compress the environmental state space. In considering the continuity of the state space and action space, the SD-TD3 algorithm is proposed in combination with the double-delayed deep deterministic policy gradient algorithm (TD3), which can accelerate the training convergence speed and improve the obstacle avoidance capability of the algorithm model. Further, to address the sparse reward problem of traditional reinforcement learning, a heuristic dynamic reward function is designed to give real-time rewards and guide the UAV to complete the task. The simulation results show that the training results of the SD-TD3 algorithm converge faster than the TD3 algorithm, and the actual results of the converged model are better. Full article

(This article belongs to the Topic Design, Simulation and New Applications of Unmanned Aerial Vehicles)

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Open AccessEditor’s ChoiceArticle

Tribodynamic Modelling of High-Speed Rolling Element Bearings in Flexible Multi-Body Environments

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Harry Questa

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Mahdi Mohammadpour

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Stephanos Theodossiades

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Colin P. Garner

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Stephen R. Bewsher

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Günter Offner

Machines 2023, 11(1), 93; https://doi.org/10.3390/machines11010093 - 11 Jan 2023

Viewed by 767

Abstract

This study presents a new flexible dynamic model for drive systems comprising lubricated bearings operating under conditions representative of electrified vehicle powertrains. The multi-physics approach importantly accounts for the tribological phenomena at the roller–race conjunction and models their effect on shaft-bearing system dynamics. [...] Read more.

This study presents a new flexible dynamic model for drive systems comprising lubricated bearings operating under conditions representative of electrified vehicle powertrains. The multi-physics approach importantly accounts for the tribological phenomena at the roller–race conjunction and models their effect on shaft-bearing system dynamics. This is achieved by embedding a non-linear lubricated bearing model within a flexible system level model; this is something which has not, to the authors’ knowledge, been reported on hitherto. The elastohydrodynamic (EHL) film is shown to increase contact deflection, leading to increased contact forces and total bearing stiffness as rotational speeds increase. Results show that for a 68 Nm hub motor operating up to 21,000 rpm, the input bearing EHL film reaches a thickness of 4.15

μ

m. The lubricant entrainment increases the roller–race contact deflection, causing the contact stiffness to increase non-linearly with speed. The contribution of the lubricant film leads to a 16.6% greater bearing stiffness at 21,000 rpm when compared to conventional dry-bearing modelling methods used in current multi-body dynamic software. This new methodology leads to more accurate dynamic response of high-speed systems necessary for the next generation of electrified vehicles. Full article

(This article belongs to the Special Issue Friction and Lubrication of Rolling Element Bearings)

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Open AccessEditor’s ChoiceArticle

Assessment of a Fully Renewable Generation System with Storage to Cost-Effectively Cover the Electricity Demand of Standalone Grids: The Case of the Canary Archipelago by 2040

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Yago Rivera-Durán

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César Berna-Escriche

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Yaisel Córdova-Chávez

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José Luis Muñoz-Cobo

Machines 2023, 11(1), 101; https://doi.org/10.3390/machines11010101 - 11 Jan 2023

Cited by 1 | Viewed by 744

Abstract

The change towards a clean electric generation system is essential to achieve the economy decarbonization goal. The Canary Islands Archipelago confronts social, environmental, and economic challenges to overcome the profound change from a fossil fuel-dependent economy to a fully sustainable renewable economy. This [...] Read more.

The change towards a clean electric generation system is essential to achieve the economy decarbonization goal. The Canary Islands Archipelago confronts social, environmental, and economic challenges to overcome the profound change from a fossil fuel-dependent economy to a fully sustainable renewable economy. This document analyzes a scenario with a totally renewable generation system and with total electrification of the economy for the Canary Islands by 2040. In addition, it also shows the significant reduction in this fully renewable system when an optimized interconnection among islands is considered. This scenario consists of a solar PV system of 11 GWp, a wind system of only 0.39 GWp, a pumped storage system of 16.64 GWh (2065 MW), and a lithium-ion battery system of 34.672 GWh (3500 MW), having a system LCOE of 10.1 cEUR/kWh. These results show the certainty of being able to use an autonomous, reliable, and fully renewable system to generate and store the energy needed to dispense with fossil fuels, thus, resulting in a system free of greenhouse gas emissions in the electricity market. In addition, the proposed system has low energy wastage (less than 20%) for a fully renewable, stand-alone, and off-grid system. Full article

(This article belongs to the Special Issue Renewable Energy Power Plants and Systems)

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Open AccessEditor’s ChoiceArticle

Stress and Corrosion Defect Identification in Weak Magnetic Leakage Signals Using Multi-Graph Splitting and Fusion Graph Convolution Networks

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Shaoxuan Zhang

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Senxiang Lu

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Xu Dong

Machines 2023, 11(1), 70; https://doi.org/10.3390/machines11010070 - 06 Jan 2023

Viewed by 582

Abstract

Weak magnetic flux leak detection is one of the most important non-destructive testing and measurement methods for pipelines. Since different defects cause different damage, it is necessary to classify the different types of defects. Traditional machine learning methods of defect type identification mainly [...] Read more.

Weak magnetic flux leak detection is one of the most important non-destructive testing and measurement methods for pipelines. Since different defects cause different damage, it is necessary to classify the different types of defects. Traditional machine learning methods of defect type identification mainly use feature analysis methods and rely on expert a priori knowledge and the ability of designers. These methods have the following weaknesses: a priori knowledge needs to be designed iteratively, and a priori knowledge design relies on expert experience. In recent years, the rapid development of deep learning methods in the field of machine vision has led to the development of defect analysis in the industry. However, most deep learning methods lack the ability to analyze both detailed information and the overall structure. In this paper, we propose graph convolution networks for splitting and fusing multiple graphs of detail graphs and a root graph. Detail information (detail graphs) provides detailed information for the detection of WMFLs. The structure information (root graph) provides structural information for the detection of WMFLs. This paper uses simulation data and experimental data to verify that the proposed method can identify stress defects and corrosion defects well. The paper explains the experimental results in detail to demonstrate the superiority of the method in industrial methods. Full article

(This article belongs to the Section Machines Testing and Maintenance)

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Open AccessEditor’s ChoiceArticle

Model Predictive Control Method for Autonomous Vehicles in Roundabouts

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Zsófia Farkas

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András Mihály

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Péter Gáspár

Machines 2023, 11(1), 75; https://doi.org/10.3390/machines11010075 - 06 Jan 2023

Viewed by 894

Abstract

This paper introduces a procedure for controlling autonomous vehicles entering roundabouts. The aim of the centralized controller is to define the velocity profile of each autonomous vehicle by which collisions can be avoided and traveling times can be minimized. To achieve these performances, [...] Read more.

This paper introduces a procedure for controlling autonomous vehicles entering roundabouts. The aim of the centralized controller is to define the velocity profile of each autonomous vehicle by which collisions can be avoided and traveling times can be minimized. To achieve these performances, a model predictive control is introduced based on the solution of an analytical calculation of traveling times spent in the roundabout and designing the autonomous vehicles’ velocity profiles in order to avoid conflict situations while ensuring a time-optimal solution. By the application of the proposed procedure, safety of autonomous vehicles can be enhanced and the possibility of a forming congestion can be minimized. The operation of the proposed method is demonstrated by a few simulation examples in the CarSim simulation environment. Full article

(This article belongs to the Special Issue Current and Future Trends in Control and Automation- Selected Papers from the 30th Mediterranean Conference on Control and Automation (MED ’22))

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Open AccessEditor’s ChoiceArticle

Multi-Objective Optimization of Magnetorheological Mount Considering Optimal Damping Force and Maximum Adjustable Coefficient

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Machines 2023, 11(1), 60; https://doi.org/10.3390/machines11010060 - 04 Jan 2023

Viewed by 614

Abstract

To address the problem of multiple working conditions and complex requirements in magnetorheological fluid (MRF) mounts, a high-precision damping characteristic optimization method is explored. Based on the parallel plate model, the equation of fluid motion in the inertial channel was established according to [...] Read more.

To address the problem of multiple working conditions and complex requirements in magnetorheological fluid (MRF) mounts, a high-precision damping characteristic optimization method is explored. Based on the parallel plate model, the equation of fluid motion in the inertial channel was established according to the Navier–Stokes equation, and the MRF mount damping characteristics were analyzed. Considering the fluid model to be suitable in the steady-state, the model was experimentally verified, and the extended equation was fitted. Multi-objective optimization design was carried out by considering the large damping force and adjustable coefficient as the optimization goal and external geometric dimensions as variables. According to results, under the radial-channel MRF mount structure, the magnet core depth has the least influence on the damping force; furthermore, the damping performance can be quickly improved by changing the height of the inertial channel. The addition of the extended equations further improved the accuracy of the fluid model. The multi-objective optimization design can improve the strength and uniformity of the flux density of the MRF mount damping gap. After optimization, the damping force is increased by 44.64%; moreover, when the current is increased from 1.5 to 1.8 A, the controllable force increases by only 2.26%, and the damping performance is fully exerted. Full article

(This article belongs to the Special Issue Noise and Vibration Control in Dynamic Systems)

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Open AccessEditor’s ChoiceArticle

Obstacle Detection by Autonomous Vehicles: An Adaptive Neighborhood Search Radius Clustering Approach

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Machines 2023, 11(1), 54; https://doi.org/10.3390/machines11010054 - 02 Jan 2023

Viewed by 878

Abstract

For autonomous vehicles, obstacle detection results using 3D lidar are in the form of point clouds, and are unevenly distributed in space. Clustering is a common means for point cloud processing; however, improper selection of clustering thresholds can lead to under-segmentation or over-segmentation [...] Read more.

For autonomous vehicles, obstacle detection results using 3D lidar are in the form of point clouds, and are unevenly distributed in space. Clustering is a common means for point cloud processing; however, improper selection of clustering thresholds can lead to under-segmentation or over-segmentation of point clouds, resulting in false detection or missed detection of obstacles. In order to solve these problems, a new obstacle detection method was required. Firstly, we applied a distance-based filter and a ground segmentation algorithm, to pre-process the original 3D point cloud. Secondly, we proposed an adaptive neighborhood search radius clustering algorithm, based on the analysis of the relationship between the clustering radius and point cloud spatial distribution, adopting the point cloud pitch angle and the horizontal angle resolution of the lidar, to determine the clustering threshold. Finally, an autonomous vehicle platform and the offline autonomous driving KITTI dataset were used to conduct multi-scene comparative experiments between the proposed method and a Euclidean clustering method. The multi-scene real vehicle experimental results showed that our method improved clustering accuracy by 6.94%, and the KITTI dataset experimental results showed that the F1 score increased by 0.0629. Full article

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Machines and Applications (IECMA 2022))

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Open AccessEditor’s ChoiceArticle

Characterization of the Anomalous Vibration Response of an Intentionally Mistuned LPT Rotor

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Salvador Rodríguez-Blanco

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Carlos Martel

Machines 2023, 11(1), 19; https://doi.org/10.3390/machines11010019 - 24 Dec 2022

Viewed by 713

Abstract

The wind tunnel facility at the Centro de Tecnologías Aeronáuticas was used to perform a set of experiments to study the effect of intentional mistuning on the forced response behavior of an aerodynamically unstable low-pressure turbine rotor. The intentional mistuning patterns were implemented [...] Read more.

The wind tunnel facility at the Centro de Tecnologías Aeronáuticas was used to perform a set of experiments to study the effect of intentional mistuning on the forced response behavior of an aerodynamically unstable low-pressure turbine rotor. The intentional mistuning patterns were implemented by adding a small extra mass to some of the blades. The forced response of the rotor was therefore expected to show two resonance peaks with similar amplitudes, corresponding, respectively, to the vibration frequencies of the blades with and without added mass. However, on the post-processing of the measurements, some anomalous behavior was observed. Near resonance, the system response was synchronous with the forcing, and the frequency sweeps exhibited two resonance peaks, but it was found that the two peaks were clearly different, with the peak at lower frequency showing a much higher vibration amplitude than the high-frequency peak, and with some blades responding at both frequencies with a similar amplitude. In order to give a correct interpretation of the experimental results, a reduced-order model is derived that takes into account only the traveling wave modes coupled by the mistuning. This model, although extremely simple, is capable of reproducing the unexpected behavior of the experiments, and gives a clean explanation of the system response. It is shown that the relative size of the mistuning with respect to the frequency difference of the involved traveling-wave modes is the key parameter for the appearance of this phenomenon. Full article

(This article belongs to the Special Issue 10th Anniversary of Machines—Feature Papers in Turbomachinery)

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Open AccessEditor’s ChoiceArticle

Advanced Motor Control for Improving the Trajectory Tracking Accuracy of a Low-Cost Mobile Robot

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Luis Mérida-Calvo

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Andrés San-Millán Rodríguez

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Francisco Ramos

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Vicente Feliu-Batlle

Machines 2023, 11(1), 14; https://doi.org/10.3390/machines11010014 - 23 Dec 2022

Cited by 1 | Viewed by 1271

Abstract

Accurate trajectory tracking is a paramount objective when a mobile robot must perform complicated tasks. In high-speed movements, time delays appear when reaching the desired position and orientation, as well as overshoots in the changes of orientation, which prevent the execution of some [...] Read more.

Accurate trajectory tracking is a paramount objective when a mobile robot must perform complicated tasks. In high-speed movements, time delays appear when reaching the desired position and orientation, as well as overshoots in the changes of orientation, which prevent the execution of some tasks. One of the aspects that most influences the tracking performance is the control system of the actuators of the robot wheels. It usually implements PID controllers that, in the case of low-cost robots, do not yield a good tracking performance owing to friction nonlinearity, hardware time delay and saturation. We propose to overcome these problems by designing an advanced process control system composed of a PID controller plus a prefilter combined with a Smith predictor, an anti-windup scheme and a Coulomb friction compensator. The contribution of this article is the motor control scheme and the method to tune the parameters of the controllers. It has been implemented in a well-known low-cost small mobile robot and experiments have been carried out that demonstrate the improvement achieved in the performance by using this control system. Full article

(This article belongs to the Special Issue Advances in Automatic Control)

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Open AccessEditor’s ChoiceArticle

Identifying Parametric Models Used to Estimate Track Irregularities of a High-Speed Railway

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Sunghoon Choi

Machines 2023, 11(1), 6; https://doi.org/10.3390/machines11010006 - 21 Dec 2022

Viewed by 446

Abstract

This study aims to identify parametric models to estimate track irregularities in high-speed railways with simple acceleration measurements. The primary contribution of current research is the development of effective parametric models with smaller parameters. These parameters are derived from the measured data via [...] Read more.

This study aims to identify parametric models to estimate track irregularities in high-speed railways with simple acceleration measurements. The primary contribution of current research is the development of effective parametric models with smaller parameters. These parameters are derived from the measured data via a specialized track geometry inspection system. An adaptive Kalman filter algorithm, using the displacement estimated from the acceleration signals as the input and measured track irregularities as the output, is applied to obtain the model’s unknown parameters. These models are applied to acceleration measured from high-speed rail vehicles in operation, and track irregularities are estimated in spatial and wavelength domains. The estimated irregularities are compared to the track geometry inspection system’s results. Full article

(This article belongs to the Section Vehicle Engineering)

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Open AccessEditor’s ChoiceArticle

A General Pose Recognition Method and Its Accuracy Analysis for 6-Axis External Fixation Mechanism Using Image Markers

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Machines 2022, 10(12), 1234; https://doi.org/10.3390/machines10121234 - 16 Dec 2022

Viewed by 705

Abstract

The 6-axis external fixation mechanism with Gough-Stewart configuration has been widely applied to the correction of long bone deformities in orthopedics. Pose recognition of the mechanism is essential for trajectory planning of bone correction, but is usually implemented by the surgeons’ experience, resulting [...] Read more.

The 6-axis external fixation mechanism with Gough-Stewart configuration has been widely applied to the correction of long bone deformities in orthopedics. Pose recognition of the mechanism is essential for trajectory planning of bone correction, but is usually implemented by the surgeons’ experience, resulting in a relatively low level of correction accuracy. This paper proposes a pose recognition method based on novel image markers, and implements accuracy analysis. Firstly, a pose description of the mechanism is established with several freely installed markers, and the layout of the markers is also parametrically described. Then, a pose recognition method is presented by identifying the orientation and position parameters using the markers. The recognition method is general in that it encompasses all possible marker layouts, and the recognition accuracy is investigated by analyzing variations in the marker layout. On this basis, layout principles for markers that achieve a desired recognition accuracy are established, and an error compensation strategy for precision improvement is provided. Finally, experiments were conducted. The results show that volume errors of pose recognition were 0.368 ± 0.130 mm and 0.151 ± 0.045°, and the correction accuracy of the fracture model after taking compensation was 0.214 ± 0.573 mm and −0.031 ± 0.161°, validating the feasibility and accuracy of the proposed methods. Full article

(This article belongs to the Special Issue Development and Applications of Parallel Robots)

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Open AccessEditor’s ChoiceArticle

Indirect Estimation of Tire Pressure on Several Road Pavements via Interacting Multiple Model Approach

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Renato Brancati

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Francesco Tufano

Machines 2022, 10(12), 1221; https://doi.org/10.3390/machines10121221 - 15 Dec 2022

Cited by 1 | Viewed by 814

Abstract

Generally, tire deflation results in a decrease in both handling performance and tire lifetime, and in fuel consumption increment. Therefore, the real-time knowledge of the pressure is important. Direct approaches via pressure sensors mounted on the rim of each tire are not practical, [...] Read more.

Generally, tire deflation results in a decrease in both handling performance and tire lifetime, and in fuel consumption increment. Therefore, the real-time knowledge of the pressure is important. Direct approaches via pressure sensors mounted on the rim of each tire are not practical, due to technical and economic reasons. Cost-effective solutions with real-time estimation of tire pressure are generally less accurate and reliable than direct ones. Dynamical estimators based on a suspension model need road surface topology information to compute disturbances on the suspension system as an input, which is typically unknown. This paper proposes an innovative approach to estimate tire pressure indirectly, without actual road surface roughness information. A vertical suspension dynamic model is used to build several unscented Kalman filters, parametrised around different road surface topologies. These estimators are combined following the Interacting Multiple Model approach, which gives an acceptable estimation of tire stiffness through a weighted average obtained from a probabilistic model. A known linear static relationship between the tire stiffness and inflation pressure is utilized to indirectly estimate the tire inflation pressure. A Monte Carlo analysis has been performed on a wide range of driving scenarios and vehicle manoeuvres. The results of the estimation have been compared to those of a single unscented Kalman filter, in order to validate the effectiveness of the proposed solution and to highlight the improved performances in monitoring tire pressure. Full article

(This article belongs to the Special Issue Feature Review Papers on Trends and Challenges in Automotive Engineering)

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Open AccessEditor’s ChoiceArticle

Sliding Mode Based Load Frequency Control and Power Smoothing of Power Systems with Wind and BESS Penetration

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Machines 2022, 10(12), 1225; https://doi.org/10.3390/machines10121225 - 15 Dec 2022

Cited by 2 | Viewed by 912

Abstract

This study aims to maintain the frequency stability of the power system penetrated by wind power. Hence, a battery energy storage system (BESS) is applied to smooth the wind power output in power systems and to enhance their load frequency control (LFC) capacity. [...] Read more.

This study aims to maintain the frequency stability of the power system penetrated by wind power. Hence, a battery energy storage system (BESS) is applied to smooth the wind power output in power systems and to enhance their load frequency control (LFC) capacity. A novel comprehensive control framework is proposed for power systems integrated with wind farms and BESS based on an adaptive fuzzy super-twisting sliding mode control (AF-SSMC) method. Firstly, the sliding functions and control laws of subsystems are designed according to different relative degrees. Then, the super-twisting algorithm is applied to suppress the chattering of the sliding mode control law. Furthermore, an adaptive fuzzy control method is used to adjust the control gains online for better control performance of the controllers. The Lyapunov stability theory is employed to prove the asymptotic stability of the subsystems. The model of an interconnected thermal power system with wind and BESS penetration is also constructed for simulation analyses. The results indicate that the AF-SSMC method effectively reduces the chattering, and the proposed framework stabilizes the frequency of the power system under system uncertainties and external disturbances. Moreover, the wind farm and BESS combined system accurately tracks a reference power to reduce wind power fluctuations. Full article

(This article belongs to the Special Issue Optimization and Control of Distributed Energy Systems)

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Open AccessEditor’s ChoiceArticle

View-Invariant Spatiotemporal Attentive Motion Planning and Control Network for Autonomous Vehicles

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Machines 2022, 10(12), 1193; https://doi.org/10.3390/machines10121193 - 09 Dec 2022

Cited by 1 | Viewed by 1238

Abstract

Autonomous driving vehicles (ADVs) are sleeping giant intelligent machines that perceive their environment and make driving decisions. Most existing ADSs are built as hand-engineered perception-planning-control pipelines. However, designing generalized handcrafted rules for autonomous driving in an urban environment is complex. An alternative approach [...] Read more.

Autonomous driving vehicles (ADVs) are sleeping giant intelligent machines that perceive their environment and make driving decisions. Most existing ADSs are built as hand-engineered perception-planning-control pipelines. However, designing generalized handcrafted rules for autonomous driving in an urban environment is complex. An alternative approach is imitation learning (IL) from human driving demonstrations. However, most previous studies on IL for autonomous driving face several critical challenges: (1) poor generalization ability toward the unseen environment due to distribution shift problems such as changes in driving views and weather conditions; (2) lack of interpretability; and (3) mostly trained to learn the single driving task. To address these challenges, we propose a view-invariant spatiotemporal attentive planning and control network for autonomous vehicles. The proposed method first extracts spatiotemporal representations from images of a front and top driving view sequence through attentive Siamese 3DResNet. Then, the maximum mean discrepancy loss (MMD) is employed to minimize spatiotemporal discrepancies between these driving views and produce an invariant spatiotemporal representation, which reduces domain shift due to view change. Finally, the multitasking learning (MTL) method is employed to jointly train trajectory planning and high-level control tasks based on learned representations and previous motions. Results of extensive experimental evaluations on a large autonomous driving dataset with various weather/lighting conditions verified that the proposed method is effective for feasible motion planning and control in autonomous vehicles. Full article

(This article belongs to the Special Issue Dynamics and Control of Autonomous Vehicles)

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Open AccessEditor’s ChoiceArticle

Wind Turbine Blade Defect Detection Based on Acoustic Features and Small Sample Size

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Machines 2022, 10(12), 1184; https://doi.org/10.3390/machines10121184 - 07 Dec 2022

Viewed by 1047

Abstract

Wind power has become an important source of electricity for both production and domestic use. However, because wind turbines often operate in harsh environments, they are prone to cracks, blisters, and corrosion of the blade surface. If these defects cannot be repaired in [...] Read more.

Wind power has become an important source of electricity for both production and domestic use. However, because wind turbines often operate in harsh environments, they are prone to cracks, blisters, and corrosion of the blade surface. If these defects cannot be repaired in time, the cracks evolve into larger fractures, which can lead to blade rupture. As such, in this study, we developed a remote non-contact online health monitoring and warning system for wind turbine blades based on acoustic features and artificial neural networks. Collecting a large number of wind turbine blade defect signals was challenging. To address this issue, we designed an acoustic detection method based on a small sample size. We employed the octave to extract defect information, and we used an artificial neural network based on model-agnostic meta-learning (MAML-ANN) for classification. We analyzed the influence of locations and compared the performance of MAML-ANN with that of traditional ANN. The experimental results showed that the accuracy of our method reached 94.1% when each class contained only 50 data; traditional ANN achieved an accuracy of only 85%. With MAML-ANN, the training is fast and the global optimal solution is automatic searched, and it can be expanded to situations with a large sample size. Full article

(This article belongs to the Special Issue Advances in Wind and Solar Energy Generation)

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Open AccessEditor’s ChoiceArticle

Configuration Design and Optimal Energy Management for Coupled-Split Powertrain Tractor

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Machines 2022, 10(12), 1175; https://doi.org/10.3390/machines10121175 - 07 Dec 2022

Cited by 1 | Viewed by 722

Abstract

High-power tractors are regarded as effective operation tools in agriculture, and plugin hybrid tractors have shown potential as agricultural machinery, due to their wide application in energy conservation. However, the allocation of the output power of the motors and engine is a challenging [...] Read more.

High-power tractors are regarded as effective operation tools in agriculture, and plugin hybrid tractors have shown potential as agricultural machinery, due to their wide application in energy conservation. However, the allocation of the output power of the motors and engine is a challenging task, given that the energy management strategy (EMS) is nonlinearly constrained. On the other hand, the structure of the continuous variable transmission (CVT) system is complicated, and affects the price of tractors. In this paper, a variable configuration of a tractor that could have the same performance as a complex CVT system is proposed. To address the EMS issues that have shown poor performance in real time, where the programming runs online, firstly a demand power prediction algorithm is proposed in a rotary tillage operation mode. Secondly, an equivalent fuel consumption minimization strategy (ECMS) is used to optimize the power distribution between the engine and the motors. In addition, the equivalent factor is optimized with an offline genetic algorithm. Thirdly, the equivalent factor is converted into a lookup table, and is used for an online power distribution with different driving mileages and state-of-charge (SOC). The simulation results indicate that the equivalent fuel consumption is reduced by 8.4% and extends the operating mileage of pure electric power. Furthermore, the error between the actual and forecasted demand power is less than 1%. The online EMS could improve the mileage of the tractor working cycle with a more feasible fuel economy based on demand power predictions. Full article

(This article belongs to the Topic Vehicle Dynamics and Control)

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