Research

Open AccessArticle

Research on a New Method of Track Turnout Identification Based on Improved Yolov5s

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Processes 2023, 11(7), 2123; https://doi.org/10.3390/pr11072123 - 16 Jul 2023

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Abstract

The modern tram track automatic cleaning car is a crucial equipment in urban rail transportation systems, effectively removing trash, dust, and other debris from the slotted tracks of trams. However, due to the complex and variable structure of turnouts, the cleaning car often [...] Read more.

The modern tram track automatic cleaning car is a crucial equipment in urban rail transportation systems, effectively removing trash, dust, and other debris from the slotted tracks of trams. However, due to the complex and variable structure of turnouts, the cleaning car often requires assistance in accurately detecting their positions. Consequently, the cleaning car needs help in adequately cleaning or bypassing turnouts, which adversely affects cleaning effectiveness and track maintenance quality. This paper presents a novel method for tracking turnout identification called PBE-YOLO based on the improved yolov5s framework. The algorithm enhances yolov5s by optimizing the lightweight backbone network, improving feature fusion methods, and optimizing the regression loss function. The proposed method is trained using a dataset of track turnouts collected through field shots on modern tram lines. Comparative experiments are conducted to analyze the performance of the improved lightweight backbone network, as well as performance comparisons and ablation experiments for the new turnout identification method. Experimental results demonstrate that the proposed PBE-YOLO method achieves a 52.71% reduction in model parameters, a 4.60% increase in mAP@0.5(%), and a 3.27% improvement in precision compared to traditional yolov5s. By improving the track turnout identification method, this paper enables the automatic cleaning car to identify turnouts’ positions accurately. This enhancement leads to several benefits, including increased automation levels, improved cleaning efficiency and quality, reduced reliance on manual intervention, and mitigation of collision risks between the cleaning car and turnouts. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

Predicting Centrifugal Pumps’ Complete Characteristics Using Machine Learning

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Jiangping Yu

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Emmanuel Akoto

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Derek Kweku Degbedzui

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Liren Hu

Processes 2023, 11(2), 524; https://doi.org/10.3390/pr11020524 - 09 Feb 2023

Viewed by 1060

Abstract

The complete characteristics of centrifugal pumps are crucial for the modeling of hydraulic transient phenomena occurring in pipe systems. However, due to the effort required to obtain these curves, pump manufacturers typically only provide basic information, particularly when the pump operates under normal [...] Read more.

The complete characteristics of centrifugal pumps are crucial for the modeling of hydraulic transient phenomena occurring in pipe systems. However, due to the effort required to obtain these curves, pump manufacturers typically only provide basic information, particularly when the pump operates under normal conditions. To acquire the full characteristic curves based on the manufacturer’s normal performance curve, a machine learning (ML) model is proposed to predict full, complete Suter curves using a pump’s specific speed with the known parts of the Suter curve. The training data for the model are sourced from the available Suter curves from laboratory experiments. Subsequently, the proposed ML model combines several types of regression models in an attempt to find the most accurate prediction in terms of the root mean square error (RMSE). The result proved highly efficient, as the experiments attained a maximum RMSE value of 0.032 across the three categories of centrifugal pumps based on their specific speeds, hence demonstrating the potential of machine learning in the study of pump characteristic curves. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

Effects of Different Influencing Factors on Temperature Distributions and Cooling Performance of Turbocharger Bearing Casing

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Bo Liu

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Bin Zhang

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Shuwan Cui

Processes 2022, 10(10), 2121; https://doi.org/10.3390/pr10102121 - 18 Oct 2022

Viewed by 948

Abstract

In order to study temperature distributions under different influencing factors and evaluate the cooling performance of the turbocharger bearing casing, water-cooling system experiments regarding the turbocharger bearing casing are carried out, and an improved fuzzy analytic hierarchy process (FAHP) evaluation method for evaluating [...] Read more.

In order to study temperature distributions under different influencing factors and evaluate the cooling performance of the turbocharger bearing casing, water-cooling system experiments regarding the turbocharger bearing casing are carried out, and an improved fuzzy analytic hierarchy process (FAHP) evaluation method for evaluating its design performance is proposed firstly. Then, the effects of various factors such as cooling-water inlet flow velocity, cooling-water inlet temperature, cooling-water pressure and exhaust temperature on the cooling performance of the bearing casing are investigated according to the experimental results. Finally, the design performance of the water-cooling system in the turbocharger bearing casing is evaluated based on the FAHP evaluation method. The results show that the turbocharger bearing casing temperature and the temperature drop rate show a decreasing trend with the increase of inlet cooling-water velocity, but that the temperature and temperature rise rate increase with the increase of the inlet temperature of cooling-water and exhaust temperature; the temperatures under the inlet velocities of 4 m/s, 5 m/s and 6 m/s are reduced by 4.1%, 5.9% and 6.7% compared with that under 3 m/s, respectively. In addition, the bearing casing temperatures firstly reduce then increase with the increase of cooling-water pressure, where the boiling heat transfer plays an important role; points 1, 2 and 3 have relatively higher temperatures than other points under all working conditions; the bearing casing temperature of six measuring points also increases under a cooling-water pressure between 0.1 MPa and 0.25 MPa. Moreover, the performance evaluation value based on the FAHP method for the turbocharger bearing casing is 87.7620, and the performance evaluation level is good, which indicates that the water-cooling system in the turbocharger bearing casing has desirable design performance. This work provides reference for the turbocharger’s design and its cooling performance enhancement. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

Analytical Research on the Bearing Characteristics of Oil Film Supplied with Constant Oil Flow Hydrostatic Turntables under Fixed Eccentric Load Condition

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Processes 2022, 10(10), 2017; https://doi.org/10.3390/pr10102017 - 06 Oct 2022

Viewed by 879

Abstract

This study was initiated in view of the phenomenon that hydrostatic turntable rails are prone to scrape damage when the liquid hydrostatic turntable is running under fixed partial load. The existing bias-load hydrostatic turntable oil film bearing characteristics are mainly calculated by using [...] Read more.

This study was initiated in view of the phenomenon that hydrostatic turntable rails are prone to scrape damage when the liquid hydrostatic turntable is running under fixed partial load. The existing bias-load hydrostatic turntable oil film bearing characteristics are mainly calculated by using the calculus integration method and CFD fluid simulation method. The calculating formula obtained by the calculus integration method is complex and inefficient. The CFD fluid simulation calculation method requires 3D modeling and meshing of the oil film, which is a tedious and time-consuming process and may not yield convergent calculation results due to improper meshing methods or boundary condition settings. In order to solve the shortage of the above calculation methods, this paper simplifies and equates the uneven thickness of the oil film of each sealing edge of the oil pad of the bias-loaded hydrostatic rotary table to the equivalent uniform thickness of the oil film, and based on this idea, the analytical calculation formula of the oil film bearing capacity, bending moment and stiffness under constant bias-load conditions of the constant-flow liquid hydrostatic rotary table is derived. In this paper, Fluent software was used to numerically simulate the oil film under this working condition, and a hydrostatic turntable test bench was established to conduct an experimental study on the biased load hydrostatic turntable; the experimental data and simulation results were compared with the results obtained from this simplified method of calculating the oil film loading characteristics. The results show that the error of oil film bearing capacity is less than 6% and the error of overturning moment is less than 7%, which has verified the validity of the calculation method. The simplified analytical calculation method proposed in this paper is used to study the influence of tilt displacement rate, lubricant flow rate and turntable speed on the basic performance parameters of oil film, which provides a theoretical basis for the study of oil film load-bearing characteristics under constant bias-load conditions of the constant-flow liquid hydrostatic turntable. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

Investigation on Safety Dynamic Evolution Mechanism of a Distributed Low Carbon Manufacturing System with Large Time Delay

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Processes 2022, 10(9), 1707; https://doi.org/10.3390/pr10091707 - 27 Aug 2022

Viewed by 771

Abstract

In order to reveal the inducing factors and safety dynamic evolution mechanism of frequent personal injury accidents under a low carbon manufacturing process, a nonlinear safety dynamic evolution model of a distributed low carbon manufacturing system with large time delay is established. The [...] Read more.

In order to reveal the inducing factors and safety dynamic evolution mechanism of frequent personal injury accidents under a low carbon manufacturing process, a nonlinear safety dynamic evolution model of a distributed low carbon manufacturing system with large time delay is established. The established model is then verified by simulation results from mathematical analysis and dynamic evolution. Moreover, qualitative analysis on nonlinear safety dynamic evolution and the trend of human–machine safety under a low carbon manufacturing process is investigated. Finally, an application case of the established model is studied. The key results are as follows: (1) There are four dynamic regions, namely the safety area I, the deterioration area II, the asymptotically stable safety area III, and the enhancement area IV of the safety ability in the interaction evolution model of carelessness and safety levels; (2) There are two singularities in the dynamic evolution model of the man–machine safety system with large time delay under a low carbon manufacturing process; (3) The equilibrium points of the human–machine safety system are E_l = (0, 0) and E₂ = (0.5333, 0.2489), while changes in the carelessness level have a serious block effect on safety development with time; (4) For the radial tire casing process, the low carbon development trend of the technological process of radial tire casing is good, but low carbon structure and management have slightly lower low carbon levels. This work provides a theoretical basis for the safety evaluation and control of the distributed low carbon manufacturing human–machine safety system with large time delay. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

Study of Torsional Vibration Bifurcation Characteristics of Direct-Drive Wind Turbine Shaft System

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Processes 2022, 10(9), 1700; https://doi.org/10.3390/pr10091700 - 26 Aug 2022

Cited by 1 | Viewed by 879

Abstract

This paper set out to establish the dynamics model of shaft torsional vibration for direct-drive wind turbine with the phenomenon of unstable shaft system torsional vibration. The stability of the equilibrium point of the dynamical model is investigated, and the Routh–Hurwitz stability criterion [...] Read more.

This paper set out to establish the dynamics model of shaft torsional vibration for direct-drive wind turbine with the phenomenon of unstable shaft system torsional vibration. The stability of the equilibrium point of the dynamical model is investigated, and the Routh–Hurwitz stability criterion is used to obtain a range of values for the bifurcation control parameters. For the stable equilibrium point, the stability domain of the system is calculated by constructing the Lyapunov function. The sensitivity analysis of system parameters is carried out to obtain the law of the effect of system parameters on system stability of the torsional vibration system. The results are substituted for example calculations, and the results verify the correctness of the theoretical analysis conclusions. It is proved that it is feasible to analyze the torsional vibration characteristics of the direct-drive wind turbine shaft system by using the principle of Routh–Hurwitz stability, etc., which provides a reference for the structural design of direct-drive wind turbine. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

An Optimization of a Turbocharger Blade Based on Fluid–Structure Interaction

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Processes 2022, 10(8), 1569; https://doi.org/10.3390/pr10081569 - 10 Aug 2022

Cited by 1 | Viewed by 1504

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The structural fracture of the compressor blade is the main cause of fatigue failure. The novelty of this paper is the creative application of bent swept-back modeling to the blade of the turbocharger impeller. This paper is based on a compressor impeller satisfying [...] Read more.

The structural fracture of the compressor blade is the main cause of fatigue failure. The novelty of this paper is the creative application of bent swept-back modeling to the blade of the turbocharger impeller. This paper is based on a compressor impeller satisfying the k-ε turbulence model. A simulation model was established in ANSYS software, the fluid–structure interaction was calculated in the three models before and after improvement, and the results were compared and analyzed. The optimized blade could improve the blade structure, reduce stress and deformation, and improve the pressurization ratio. In this paper, the optimization scheme of different parameters was discussed in line with the optimal solution. Based on the combination of fuzzy and grey correlation theory, it was concluded that the correlation between pressure and total deformation was higher than that of equivalent stress, and these two values reached 0.8596 and 0.8001, respectively. The results showed that the pressure and total deformation were significantly related to the flow rate. It provides a feasible scheme for further improvement of the supercharger compressor. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

Research on an Improved Sliding Mode Observer for Speed Estimation in Permanent Magnet Synchronous Motor

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Zhiqiang Liu

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Wenkai Chen

Processes 2022, 10(6), 1182; https://doi.org/10.3390/pr10061182 - 13 Jun 2022

Cited by 6 | Viewed by 1388

Abstract

Aimed at the problems of system chattering and large observation errors in the sensorless control of a permanent magnet synchronous motor (PMSM) based on a traditional sliding mode observer (SMO), a combined reaching law algorithm based on the exponential reaching law and arcsine [...] Read more.

Aimed at the problems of system chattering and large observation errors in the sensorless control of a permanent magnet synchronous motor (PMSM) based on a traditional sliding mode observer (SMO), a combined reaching law algorithm based on the exponential reaching law and arcsine saturation function reaching law is proposed to improve the sliding mode observer. An appropriate positive real number is taken and compared with the product of controller gain and stator current observation error to judge the system position in sliding mode motion. In the early stage of sliding mode motion, the exponential reaching law is utilized, and then, in the latter and stable stages of sliding mode motion, the arcsine saturation function reaching law is used. The stability of the observer is proved by Lyapunov theory. The simulation and experimental data show that the speed error of the sliding mode observer based on the combined reaching law is reduced by 80% compared with the traditional sliding mode observer, and the chattering problem is also improved. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

Lightweight Design and Experimental Study of Ceramic Composite Armor

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Processes 2022, 10(6), 1056; https://doi.org/10.3390/pr10061056 - 25 May 2022

Cited by 2 | Viewed by 1811

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Ceramic/fiber composite armor is a hot research topic of bulletproof equipment. The lightweight design of ceramic materials and structures has attracted much attention. In this work, in the light of the remarkable performance of ceramic against elastic and oblique penetration, a novel honeycomb [...] Read more.

Ceramic/fiber composite armor is a hot research topic of bulletproof equipment. The lightweight design of ceramic materials and structures has attracted much attention. In this work, in the light of the remarkable performance of ceramic against elastic and oblique penetration, a novel honeycomb ceramic panel with a hexagonal prism and spherical body was designed. The splicing ceramic/fiber composite plate was bonded with a PE plate. The splicing ceramic/fiber composite was prepared, and the target test of the composite was conducted. The results show that the bulletproof performance of the hexagonal prism spherical crown ceramic/fiber composite plate is better than that of the conventional ceramic/fiber composite plate of the same thickness. The honeycomb spherical crown structure of the ceramic surface can convert the nominal forward penetration into the actual oblique penetration. This surface structure provides an effective lightweight design of ceramic/fiber composite armor. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

A GAPN Approach for the Flexible Job-Shop Scheduling Problem with Indirect Energy and Time-of-Use Electricity Pricing

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Processes 2022, 10(5), 832; https://doi.org/10.3390/pr10050832 - 22 Apr 2022

Cited by 2 | Viewed by 1092

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The flexible job-shop scheduling problem with indirect energy and time-of-use (ToU) electricity pricing (FJSP-IT) is investigated. Considering the production cost, which includes the indirect energy cost, direct energy cost and time cost, the cost evaluation model under ToU pricing is built. To minimize [...] Read more.

The flexible job-shop scheduling problem with indirect energy and time-of-use (ToU) electricity pricing (FJSP-IT) is investigated. Considering the production cost, which includes the indirect energy cost, direct energy cost and time cost, the cost evaluation model under ToU pricing is built. To minimize the total production cost of the FJSP-IT, an approach based on a genetic algorithm and Petri nets (GAPN) is presented. Under this approach, indirect energy and direct energy are modeled with Petri net (PN) nodes, the operation time is evaluated through PN simulation, and resource allocation is fine-tuned through genetic operations. A group of heuristic operation time policies, especially the exhausting subsection policy and two mixed policies, are presented to adapt to the FJSP-IT with vague cost components. Experiments were performed on a data set generated from the banburying shop of a rubber tire plant, and the results show that the proposed GAPN approach has good convergence. Using the proposed operation time policies makes it possible to save 10.81% on the production cost compared to using the single off-peak first or passive delay policy, and considering indirect energy makes it possible to save at least 2.09% on the production cost compared to ignoring indirect energy. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

Evaluation Residual Compressive Strength of Tunnel Lining Concrete Structure after Fire Damage Based on Ultrasonic Pulse Velocity and Shear-Wave Tomography

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Processes 2022, 10(3), 560; https://doi.org/10.3390/pr10030560 - 13 Mar 2022

Cited by 3 | Viewed by 1553

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In this study, ultrasonic pulse velocity (UPV) and ultrasonic shear-wave tomography are combined to measure the residual compressive strength (RCS) of small-scale lining concrete blocks and to detect inner defects in the lining structure. The characteristics of and variations in the RCS of [...] Read more.

In this study, ultrasonic pulse velocity (UPV) and ultrasonic shear-wave tomography are combined to measure the residual compressive strength (RCS) of small-scale lining concrete blocks and to detect inner defects in the lining structure. The characteristics of and variations in the RCS of test blocks after being exposed to elevated temperatures (200–800 °C) and constant heating times (2 h, 3 h, and 4 h) were studied. At 800 °C, the RCS values reduced by 64.4%, 69.2%, and 74.6% at heating times of 2 h, 3 h, and 4 h. Scanning electron microscopy (SEM) was used for the micro-phase analysis of the samples that had been exposed to high temperatures. The heating time and RCS as well as the SEM micro-structure relationship were compared. Finally, a tunnel lining slab sample was designed to simulate the post-fire damage inside the blocks. Additionally, shear-wave tomography with 32 probes was able to detect the ϕ10 mm void defects at a depth of 200 mm. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

Investigation on Energy-Effectiveness Enhancement of Medium-Frequency Induction Furnace Based on an Adaptive Chaos Immune Optimization Algorithm with Mutative Scale

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Processes 2022, 10(3), 491; https://doi.org/10.3390/pr10030491 - 28 Feb 2022

Viewed by 1624

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Based on the chaos algorithm and immune algorithm theory, an adaptive chaotic immune optimization algorithm (ACIOA) with a mutative scale was proposed and subsequently validated by the experiment result in this paper, and then the adaptive chaotic immune optimization algorithm with mutative scale [...] Read more.

Based on the chaos algorithm and immune algorithm theory, an adaptive chaotic immune optimization algorithm (ACIOA) with a mutative scale was proposed and subsequently validated by the experiment result in this paper, and then the adaptive chaotic immune optimization algorithm with mutative scale was applied to investigate the performance characteristics of the medium-frequency induction furnace. The obtained results include the effects on the performance characteristics of a medium-frequency induction furnace of the diameter of the heated cylindrical material, the thickness of the crucible wall, the fullness degree of the induction coil, the ratio of diameter to current penetration depth, and the power frequency. The results showed that the optimization algorithm could continuously modify the variable search space and take the optimal number of cycles as the control index to carry out the search. In addition, the suitable ratio of diameter to current penetration depth was between 3.5 and 6.0, and was beneficial to the improvements of in power factor and thermal efficiency. This method had the characteristics of small calculation delay, high anti-noise ability, and high detection rate. Moreover, the maximum errors of KFF, Random, and PSO were 6.4%, 6.2%, and 5.4%, respectively. The improved method had good estimation accuracy and an excellent global optimization. Meanwhile, the suitable ratio of diameter to current penetration depth, the thickness of crucible wall, and power frequency were beneficial to the improvements in power factor and thermal efficiency. Thus, the finding is helpful as a guide to determining the design of a medium-frequency induction furnace, which may be of interest for improvements in performance under different operating conditions. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

A Spatio-Temporal Deep Learning Network for the Short-Term Energy Consumption Prediction of Multiple Nodes in Manufacturing Systems

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Processes 2022, 10(3), 476; https://doi.org/10.3390/pr10030476 - 26 Feb 2022

Cited by 2 | Viewed by 1653

Abstract

Short-term energy prediction plays an important role in green manufacturing in the industrial internet environment and has become the basis of energy wastage identification, energy-saving plans and energy-saving control. However, the short-term energy prediction of multiple nodes in manufacturing systems is still a [...] Read more.

Short-term energy prediction plays an important role in green manufacturing in the industrial internet environment and has become the basis of energy wastage identification, energy-saving plans and energy-saving control. However, the short-term energy prediction of multiple nodes in manufacturing systems is still a challenging issue owing to the fuzzy material flow (spatial relationship) and the dynamic production rhythm (temporal relationship). To obtain the complex spatial and temporal relationships, a spatio-temporal deep learning network (STDLN) method is presented for the short-term energy consumption prediction of multiple nodes in manufacturing systems. The method combines a graph convolutional network (GCN) and a gated recurrent unit (GRU) and predicts the future energy consumption of multiple nodes based on prior knowledge of material flow and the historical energy consumption time series. The GCN is aimed at capturing spatial relationships, with the material flow represented by a topology model, and the GRU is aimed at capturing dynamic rhythm from the energy consumption time series. To evaluate the method presented, several experiments were performed on the power consumption dataset of an aluminum profile plant. The results show that the method presented can predict the energy consumption of multiple nodes simultaneously and achieve a higher performance than methods based on the GRU, GCN, support vector regression (SVR), etc. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

Splitting Physical Exergy by Its Feasible Working Ways

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Processes 2021, 9(11), 2091; https://doi.org/10.3390/pr9112091 - 22 Nov 2021

Cited by 1 | Viewed by 1041

Abstract

This paper analyzed the problems associated with physical exergy splitting, and based on this, presented a new splitting method. This new method splits the physical exergy into three parts according to the feasible working ways, i.e.,: the direct, indirect, and adaptive exergy. The [...] Read more.

This paper analyzed the problems associated with physical exergy splitting, and based on this, presented a new splitting method. This new method splits the physical exergy into three parts according to the feasible working ways, i.e.,: the direct, indirect, and adaptive exergy. The computational method and the physical meaning of the three exergy parts were presented in detail in terms of graphic representation and mathematical derivation. Then, it was applied to the exergy analysis of a thermal power cycle. The results show that compared with the conventional method which splits the physical exergy into thermal and mechanical parts, the current exergy splitting method can better represent the change rule of the working ability of the real working stream in the cycle and the influence of some operation parameters, such as the turbine inlet temperature, on the real working ability. The study suggests that the new method can make the exergy analysis more helpful and guidable in its applications. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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Open AccessArticle

Probabilistic Vulnerability Assessment of Transmission Lines Considering Cascading Failures

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Processes 2021, 9(11), 1994; https://doi.org/10.3390/pr9111994 - 08 Nov 2021

Cited by 1 | Viewed by 1031

Abstract

The prevention of cascading failures and large-scale power outages of power grids by identifying weak links has become one of the key topics in power systems research. In this paper, a vulnerability radius index is proposed to identify the initial fault, and a [...] Read more.

The prevention of cascading failures and large-scale power outages of power grids by identifying weak links has become one of the key topics in power systems research. In this paper, a vulnerability radius index is proposed to identify the initial fault, and a fault chain model of cascading failure is developed with probabilistic attributes to identify the set of fault chains that have a significant impact on the safe and stable operation of power grids. On this basis, a method for evaluating the vulnerability of transmission lines based on a multi-criteria decision analysis is proposed, which can quickly identify critical transmission lines in the process of cascading failure. Finally, the proposed model and method for identifying vulnerable lines during the cascading failure process is demonstrated on the IEEE-118 bus system. Full article

(This article belongs to the Special Issue Green Manufacturing and Low-Carbon Control of Mechanical and Electrical Products)

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