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Reliability of Modern Electro-Mechanical Systems

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Multidisciplinary Applications".

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 27132

Special Issue Editors


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Guest Editor

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Guest Editor
College of Engineering, Najran University, Najran 61441, Saudi Arabia
Interests: diagnostics and prognostics; pattern recognition; statistical analysis of big data; machine fault diagnostics; non-destructive testing; condition monitoring; Internet of things; artificial intelligence; industrial electronics; smart cities and smart healthcare
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Electrical and Computer Engineering, University of Texas at El Paso, 500 West University Avenue, El Paso, TX 79968, USA
Interests: biomedical engineering; mechatronics systems engineering; robotics and automation; electrical measurements of non-electrical quantities; machine vision and pattern recognition; applications of soft computing; sensors (validation, fusion)
Special Issues, Collections and Topics in MDPI journals

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School of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
Interests: fault diagnosis; vibration analysis; measurement; mechanical engineering; diesel engines

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Department of Electrical Engineering, Universitat de València, 46022 Valencia, Spain
Interests: electric motors; fault diagnosis; transient analysis; signal processing; wavelet analysis; infrared thermography; time-frequency transforms
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The proposed Special Issue will cover advanced research in system design and fault diagnostics techniques based on information systems, entropy features, and pattern recognition. The protection of mechanical systems, under-water network systems, intelligent transportation systems and electrical power distribution systems is vital to maintain reliable operations. The advanced algorithms of Artificial Intelligence (AI), wireless sensors networks, and the Internet of Things (IoT) have brought a great revolution in the area of machine design, its installation, and safe operation. Due to enormous electric energy consumptions, the reliability of critical systems operating in a harsh industrial environment has been a great challenge in many industrial applications. It is especially important where an unexpected breakdown might result in the interruption of critical services such as military operations, transportation, municipality, aviation and medical applications. The unexpected breakdowns of the electro-mechanical systems cause a great deal of unacceptable production loss. It is intolerable in applications that are vital for the industry. Consequently, detecting initial failures and replacing damaged parts according to the schedule will prevent the problems of unexpected breakdowns of the electro-mechanical systems. Minimum downtime and high production have been the goal of every industry.

The purpose of this Special Issue is to present some of the latest innovations for the safety of the mechanical systems, under-water network systems, intelligent transportation systems, robotics and electrical power distribution systems, both theoretically and practically. It covers various topics related to machine design, software and hardware integration, condition monitoring, fault diagnostics & prognostics, signal processing, instrumentation and measurements and intelligent transportation systems.

Potential topics include but are not limited to the following:

  • Modern machines design
  • Maximum entropy features for fault diagnostic of machines
  • AI-based fault diagnostics and prognostics
  • Application of Shannon entropy in machine health diagnostics
  • IoT based system design
  • Non-destructive testing
  • Reliability of the modern machines
  • Reliability of the intelligent transportation system
  • Mechanical System Design
  • Electronic System Design
  • Electrical System Design
  • Mechatronics System Design
  • Power System Reliability
  • Power System Reliability
  • Reliability and Controllability of the Smart Grids

Dr. Adam Glowacz
Dr. Muhammad Irfan
Dr. Thompson Sarkodie-Gyan
Dr. Zhixiong Li
Prof. Dr. Jose A Antonino-Daviu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (10 papers)

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Research

13 pages, 4509 KiB  
Article
Optimum Placement of Distribution Generation Units in Power System with Fault Current Limiters Using Improved Coyote Optimization Algorithm
by Hisham Alghamdi
Entropy 2021, 23(6), 655; https://doi.org/10.3390/e23060655 - 24 May 2021
Cited by 6 | Viewed by 1675
Abstract
Electric power frameworks become intensely loaded because of the expanded power demand, and as a result, the power system faces great power losses and fault currents. The integration of Distribution Generation (DG) units plays a key role in minimizing the load pressure on [...] Read more.
Electric power frameworks become intensely loaded because of the expanded power demand, and as a result, the power system faces great power losses and fault currents. The integration of Distribution Generation (DG) units plays a key role in minimizing the load pressure on a power system. DGs are transmitted with a high fault current, which surpasses the evaluations of circuit breakers. This paper presents various DG units’ optimal placement with Fault Current Limiters (FCLs) in different phases. The Improved Coyote Optimize Algorithm (ICOA) and Electrical Transient Analyzer Program (ETAP) are assessed for the proposed technique in terms of normal and faulty working status. Similarly, to enhance the efficiency of a distribution system, a fuzzy-based multi-objective mechanism is applied. The proposed method is employed on an IEEE 21-bus and 28-bus distribution system. The simulation analysis proved that the power losses and fault levels are reduced at an acceptable level. Full article
(This article belongs to the Special Issue Reliability of Modern Electro-Mechanical Systems)
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18 pages, 3411 KiB  
Article
Research on Multi-Dimensional Optimal Location Selection of Maintenance Station Based on Big Data of Vehicle Trajectory
by Shoujing Zhang, Fujiao Tong, Mengdan Li, Shoufeng Jin and Zhixiong Li
Entropy 2021, 23(5), 495; https://doi.org/10.3390/e23050495 - 21 Apr 2021
Cited by 2 | Viewed by 1388
Abstract
In order to rationally lay out the location of automobile maintenance service stations, a method of location selection of maintenance service stations based on vehicle trajectory big data is proposed. Taking the vehicle trajectory data as the demand points, the demand points are [...] Read more.
In order to rationally lay out the location of automobile maintenance service stations, a method of location selection of maintenance service stations based on vehicle trajectory big data is proposed. Taking the vehicle trajectory data as the demand points, the demand points are divided according to the region by using the idea of zoning, and the location of the second-level maintenance station is selected for each region. The second-level maintenance stations selected in the whole country are set as the demand points of the first-level maintenance stations. Considering the objectives of the two dimensions of cost and service level, the location model of the first-level maintenance stations under two-dimensional programming is established, and the improved particle swarm optimization algorithm and immune algorithm, respectively, are used to solve the problem. In this way, the first-level maintenance stations in each region are obtained. The example verification shows that the location selection results for the maintenance stations using the vehicle trajectory big data are reasonable and closer to the actual needs. Full article
(This article belongs to the Special Issue Reliability of Modern Electro-Mechanical Systems)
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18 pages, 9188 KiB  
Article
Porcelain Insulator Crack Location and Surface States Pattern Recognition Based on Hyperspectral Technology
by Yiming Zhao, Jing Yan, Yanxin Wang, Qianzhen Jing and Tingliang Liu
Entropy 2021, 23(4), 486; https://doi.org/10.3390/e23040486 - 20 Apr 2021
Cited by 8 | Viewed by 2906
Abstract
A porcelain insulator is an important part to ensure that the insulation requirements of power equipment can be met. Under the influence of their structure, porcelain insulators are prone to mechanical damage and cracks, which will reduce their insulation performance. After a long-term [...] Read more.
A porcelain insulator is an important part to ensure that the insulation requirements of power equipment can be met. Under the influence of their structure, porcelain insulators are prone to mechanical damage and cracks, which will reduce their insulation performance. After a long-term operation, crack expansion will eventually lead to breakdown and safety hazards. Therefore, it is of great significance to detect insulator cracks to ensure the safe and reliable operation of a power grid. However, most traditional methods of insulator crack detection involve offline detection or contact measurement, which is not conducive to the online monitoring of equipment. Hyperspectral imaging technology is a noncontact detection technology containing three-dimensional (3D) spatial spectral information, whereby the data provide more information and the measuring method has a higher safety than electric detection methods. Therefore, a model of positioning and state classification of porcelain insulators based on hyperspectral technology is proposed. In this model, image data were used to extract edges to locate cracks, and spectral information was used to classify the surface states of porcelain insulators with EfficientNet. Lastly, crack extraction was realized, and the recognition accuracy of cracks and normal states was 96.9%. Through an analysis of the results, it is proven that the crack detection method of a porcelain insulator based on hyperspectral technology is an effective non-contact online monitoring approach, which has broad application prospects in the era of the Internet of Things with the rapid development of electric power. Full article
(This article belongs to the Special Issue Reliability of Modern Electro-Mechanical Systems)
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14 pages, 729 KiB  
Article
Maximum Entropy Approach to Reliability of Multi-Component Systems with Non-Repairable or Repairable Components
by Yi-Mu Du, Jin-Fu Chen, Xuefei Guan and C. P. Sun
Entropy 2021, 23(3), 348; https://doi.org/10.3390/e23030348 - 15 Mar 2021
Cited by 6 | Viewed by 1818
Abstract
The degradation and recovery processes are multi-scale phenomena in many physical, engineering, biological, and social systems, and determine the aging of the entire system. Therefore, understanding the interplay between the two processes at the component level is the key to evaluate the reliability [...] Read more.
The degradation and recovery processes are multi-scale phenomena in many physical, engineering, biological, and social systems, and determine the aging of the entire system. Therefore, understanding the interplay between the two processes at the component level is the key to evaluate the reliability of the system. Based on the principle of maximum entropy, an approach is proposed to model and infer the processes at the component level, and is applied to repairable and non-repairable systems. By incorporating the reliability block diagram, this approach allows for integrating the information of network connectivity and statistical moments to infer the hazard or recovery rates of the degradation or recovery processes. The overall approach is demonstrated with numerical examples. Full article
(This article belongs to the Special Issue Reliability of Modern Electro-Mechanical Systems)
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13 pages, 1881 KiB  
Article
Fault Diagnosis of Permanent Magnet Synchronous Motor Based on Stacked Denoising Autoencoder
by Xiaowei Xu, Jingyi Feng, Liu Zhan, Zhixiong Li, Feng Qian and Yunbing Yan
Entropy 2021, 23(3), 339; https://doi.org/10.3390/e23030339 - 12 Mar 2021
Cited by 6 | Viewed by 2075
Abstract
As a complex field-circuit coupling system comprised of electric, magnetic and thermal machines, the permanent magnet synchronous motor of the electric vehicle has various operating conditions and complicated condition environment. There are various forms of failure, and the signs of failure are crossed [...] Read more.
As a complex field-circuit coupling system comprised of electric, magnetic and thermal machines, the permanent magnet synchronous motor of the electric vehicle has various operating conditions and complicated condition environment. There are various forms of failure, and the signs of failure are crossed or overlapped. Randomness, secondary, concurrency and communication characteristics make it difficult to diagnose faults. Meanwhile, the common intelligent diagnosis methods have low accuracy, poor generalization ability and difficulty in processing high-dimensional data. This paper proposes a method of fault feature extraction for motor based on the principle of stacked denoising autoencoder (SDAE) combined with the support vector machine (SVM) classifier. First, the motor signals collected from the experiment were processed, and the input data were randomly damaged by adding noise. Furthermore, according to the experimental results, the network structure of stacked denoising autoencoder was constructed, the optimal learning rate, noise reduction coefficient and the other network parameters were set. Finally, the trained network was used to verify the test samples. Compared with the traditional fault extraction method and single autoencoder method, this method has the advantages of better accuracy, strong generalization ability and easy-to-deal-with high-dimensional data features. Full article
(This article belongs to the Special Issue Reliability of Modern Electro-Mechanical Systems)
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20 pages, 9166 KiB  
Article
Thermally Driven Flow of Water in Partially Heated Tall Vertical Concentric Annulus
by Jawed Mustafa, Saeed Alqaed and Mohammad Altamush Siddiqui
Entropy 2020, 22(10), 1189; https://doi.org/10.3390/e22101189 - 21 Oct 2020
Cited by 18 | Viewed by 3103
Abstract
Computational fluid dynamics (CFD) has become effective and crucial to several applications in science and engineering. The dynamic behavior of buoyancy induced flow of water in partially heated tall open-ended vertical annulus is analyzed based on a CFD technique. For a vertical annulus, [...] Read more.
Computational fluid dynamics (CFD) has become effective and crucial to several applications in science and engineering. The dynamic behavior of buoyancy induced flow of water in partially heated tall open-ended vertical annulus is analyzed based on a CFD technique. For a vertical annulus, the natural convective heat transfer has a broad application in engineering. The annulus is the most common structure used in various heat transmission systems, from the basic heat transfer device to the most sophisticated atomic reactors. The annular test sections of such a large aspect ratio are of practical importance in the design of equipment’s associated with the reactor systems. However, depending on the geometrical structure and heating conditions, it exhibits different flow behavior. The annulus may either be closed or open-ended. In this study, we carry out CFD analysis to examine the thermodynamics properties and the detailed thermal induced flow behavior of the water in Tall open-ended vertical concentric annuli. The purpose of this study is to evaluate the impact of a partially heating on mechanical properties and design parameters like Nusselt number, mass flow rate and pressure defect. For Rayleigh number ranging from 4.4 × 103 to 6.6 × 104, while the Prandtl number is 6.43, the numerical solution was obtained. The modelling result showing the measurement and transient behavior of different parameters is presented. The numerical results would be both qualitatively and quantitatively validated. The presentation of unstable state profiles and heat variables along the annulus are also discussed. Full article
(This article belongs to the Special Issue Reliability of Modern Electro-Mechanical Systems)
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15 pages, 11497 KiB  
Article
DSP-Assisted Nonlinear Impairments Tolerant 100 Gbps Optical Backhaul Network for Long-Haul Transmission
by Muhammad Irfan, Farman Ali, Fazal Muhammad, Usman Habib, Abdullah S. Alwadie, Adam Glowacz, Ziaul Haq Abbas and Eliasz Kańtoch
Entropy 2020, 22(9), 1062; https://doi.org/10.3390/e22091062 - 22 Sep 2020
Cited by 5 | Viewed by 3071
Abstract
High capacity long haul communication and cost-effective solutions for low loss transmission are the major advantages of optical fibers, which makes them a promising solution to be used for backhaul network transportation. A distortion-tolerant 100 Gbps framework that consists of long haul and [...] Read more.
High capacity long haul communication and cost-effective solutions for low loss transmission are the major advantages of optical fibers, which makes them a promising solution to be used for backhaul network transportation. A distortion-tolerant 100 Gbps framework that consists of long haul and high capacity transport based wavelength division multiplexed (WDM) system is investigated in this paper, with an analysis on different design parameters to mitigate the amplified spontaneous emission (ASE) noise and nonlinear effects due to the fiber transmission. The performance degradation in the presence of non-linear effects is evaluated and a digital signal processing (DSP) assisted receiver is proposed in order to achieve bit error rate (BER) of 1.56 × 106 and quality factor (Q-factor) of 5, using 25 and 50 GHz channel spacing with 90 μm2 effective area of the optical fiber. Analytical calculations of the proposed WDM system are presented and the simulation results verify the effectiveness of the proposed approach in order to mitigate non-linear effects for up to 300 km length of optical fiber transmission. Full article
(This article belongs to the Special Issue Reliability of Modern Electro-Mechanical Systems)
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16 pages, 1654 KiB  
Article
A Reliable Auto-Robust Analysis of Blood Smear Images for Classification of Microcytic Hypochromic Anemia Using Gray Level Matrices and Gabor Feature Bank
by Bakht Azam, Sami Ur Rahman, Muhammad Irfan, Muhammad Awais, Osama Mohammed Alshehri, Ahmed Saif, Mohammed Hassan Nahari and Mater H. Mahnashi
Entropy 2020, 22(9), 1040; https://doi.org/10.3390/e22091040 - 17 Sep 2020
Cited by 4 | Viewed by 4335
Abstract
Accurate blood smear quantification with various blood cell samples is of great clinical importance. The conventional manual process of blood smear quantification is quite time consuming and is prone to errors. Therefore, this paper presents automatic detection of the most frequently occurring condition [...] Read more.
Accurate blood smear quantification with various blood cell samples is of great clinical importance. The conventional manual process of blood smear quantification is quite time consuming and is prone to errors. Therefore, this paper presents automatic detection of the most frequently occurring condition in human blood—microcytic hyperchromic anemia—which is the cause of various life-threatening diseases. This task has been done with segmentation of blood contents, i.e., Red Blood Cells (RBCs), White Blood Cells (WBCs), and platelets, in the first step. Then, the most influential features like geometric shape descriptors, Gray Level Co-occurrence Matrix (GLCM), Gray Level Run Length Matrix (GLRLM), and Gabor features (mean squared energy and mean amplitude) are extracted from each of the RBCs. To discriminate the cells as hypochromic microcytes among other RBC classes, scanning is done at angles (0, 45, 90, and 135). To achieve high-level accuracy, Adaptive Synthetic (AdaSyn) sampling for imbalance learning is used to balance the datasets and locality sensitive discriminant analysis (LSDA) technique is used for feature reduction. Finally, upon using these features, classification of blood cells is done using the multilayer perceptual model and random forest learning algorithms. Performance in terms of accuracy was 96%, which is better than the performance of existing techniques. The final outcome of this work may be useful in the efforts to produce a cost-effective screening scheme that could make inexpensive screening for blood smear analysis available globally, thus providing early detection of these diseases. Full article
(This article belongs to the Special Issue Reliability of Modern Electro-Mechanical Systems)
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16 pages, 42052 KiB  
Article
Partitioned Stator Switched Flux Machine: Novel Winding Configurations
by Muhammad Irfan, Naveed Ur Rehman, Faisal Khan, Fazal Muhammad, Abdullah S. Alwadie and Adam Glowacz
Entropy 2020, 22(9), 920; https://doi.org/10.3390/e22090920 - 22 Aug 2020
Cited by 1 | Viewed by 2616
Abstract
Torque density is one of the major limiting factors in machine design. In this paper, we propose the hybrid excited partitioned stator switched flux machine3 (HE-PSSFM3). In HE-PSSFM3, armature winding is positioned on the outer stator whereas the permanent magnet (PM) and field [...] Read more.
Torque density is one of the major limiting factors in machine design. In this paper, we propose the hybrid excited partitioned stator switched flux machine3 (HE-PSSFM3). In HE-PSSFM3, armature winding is positioned on the outer stator whereas the permanent magnet (PM) and field winding are placed at the inner stator, while the rotor is free from excitation sources and armature winding. Moreover, concentrated field winding is replaced by toroidal winding. The power splitting ratio between two stators/rotor pole combinations is analytically optimized and are validated through genetic algorithm (GA) in order to enhance average torque and flux regulation capability. The electromagnetic characteristics of the improved and initial design are evaluated and compared with existing designs, i.e., HE-PSSFM1 and HE-PSSFM2. The proposed HE-PSSFM3 has achieved high average torque, i.e., 2.0015 Nm, at same armature and field current densities of 5 A/mm2. The results show that the average torques of the proposed design are 35% and 15% greater than HE-PSSFM1 and HE-PSSFM2, respectively. Furthermore, the analysis of various parameters such as flux linkage, flux regulation, electromagnetic performances, cogging torque, back EMF, electromagnetic torque, and torque ripples are investigated using two dimensional (2D) finite element analysis (FEA). Moreover, the simulation results of the proposed design are validated through GA and analytical modeling. Full article
(This article belongs to the Special Issue Reliability of Modern Electro-Mechanical Systems)
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12 pages, 3686 KiB  
Article
Design and Analysis of the IGBT Heat Dissipation Structure Based on Computational Continuum Mechanics
by Xin Lin, Huawei Wu, Zhen Liu, Baosheng Ying, Congjin Ye, Yuanjin Zhang and Zhixiong Li
Entropy 2020, 22(8), 816; https://doi.org/10.3390/e22080816 - 26 Jul 2020
Cited by 5 | Viewed by 2909
Abstract
With the trend of high integration and high power of insulated gate bipolar transistor (IGBT) components, strict requirements have been placed on the heat dissipation capabilities of the IGBT devices. On the basis of traditional rectangular fins, this paper developed two new types [...] Read more.
With the trend of high integration and high power of insulated gate bipolar transistor (IGBT) components, strict requirements have been placed on the heat dissipation capabilities of the IGBT devices. On the basis of traditional rectangular fins, this paper developed two new types of heat-dissipating fins to meet the high requirements of heat dissipation for the IGBT devices. One is the rectangular radiator with a groove length of 2.5 mm and a width of 0.85 mm, the other is the arc radiator with the angle of 125 arc angle, 0.8 mm arc height, and 1.4 mm circle radius. After theoretically calculating the IGBT junction temperature, numerical simulations have been implemented to verify the theoretical result. The commercial CFD software, STAR-CCM+, was employed to simulate the heat dissipation characteristics of the IGBT module under different wind speeds, power, and fin structures. By analyzing the temperature field and vector field of the IGBT module, the analysis results demonstrate that the error between the simulation result and the theoretical calculation is within 5%, which proves the feasibility of the newly designed heat-dissipating fins. When the wind speed is 12.5 m/s, the power is 110 W, the fin height is 31.2 mm, and the fin thickness is 2.3 mm, the rectangular radiator can achieve the best heat dissipation performance. Full article
(This article belongs to the Special Issue Reliability of Modern Electro-Mechanical Systems)
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