Next Issue
Volume 10, March
Previous Issue
Volume 10, January

Machines, Volume 10, Issue 2 (February 2022) – 93 articles

Cover Story (view full-size image): The ball-and-socket (B&S) stiffness of tilting pad journal bearings (TPJB) is still estimated by means of Hertzian formulas. Recently, some authors have used the finite element method, but it seems that nothing has been done experimentally to date. To fill this gap, a test rig was realized by equipping the grippers of a tensile universal testing machine with specifically designed interfaces and different displacement sensors. The experimental compression results were best fitted to obtain an analytical displacement—load curve, deriving which the stiffness of a TPJB B&S pivot was evaluated. Preliminary compression results are presented and compared with the analytical ones obtained using Hertz’s formula showing significant differences for the B&S conformal contact. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
Order results
Result details
Section
Select all
Export citation of selected articles as:
Article
Mechanism Analysis of Time-Dependent Characteristic of Dynamic Errors of Machine Tools
Machines 2022, 10(2), 160; https://doi.org/10.3390/machines10020160 - 21 Feb 2022
Viewed by 605
Abstract
The Dynamic Errors (DEs) of individual axes present Time-dependent Characteristics (TDCs) because the setpoints, as the input of the servo feed system, change in velocity, acceleration and jerk during the feed motion. Deep insight into the TDC contributes to the effective control of [...] Read more.
The Dynamic Errors (DEs) of individual axes present Time-dependent Characteristics (TDCs) because the setpoints, as the input of the servo feed system, change in velocity, acceleration and jerk during the feed motion. Deep insight into the TDC contributes to the effective control of DEs. However, up to now, mechanism analysis about the TDCs of DEs are indistinct and inadequate due to a lack of analysis on the TDC of setpoint frequency. So, in this study, the mechanism of the TDC of DE is investigated by extracting the TDC of setpoint frequency. Firstly, the servo dynamics model is established for presenting the DE and its respective components, the Dynamic Error Inside Servo-loop (DEIS) (tracking error) and the Dynamic Error Outside Servo-loop (DEOS) under to and fro motions. Secondly, time–frequency analysis is carried out on the setpoints of the to and fro motions to present a TDC of setpoint frequency which is described as the Time-dependent Setpoint Bandwidth (TDSB) and the Time-dependent Potential Excitation (TDPE). Finally, the correlation between the TDSBs and DEISs and the correlation between the TDPEs and DEOSs are investigated, respectively. On these bases, the mechanism of the TDC of DE is analyzed. The results show that the TDSB, which is related to the acceleration of setpoints, accounts for the TDC of the DEIS; that the TDPE, which is related to the jerk of setpoints, accounts for the TDC of the DEOS in vibration-form; and that the TDC of transient-form DEOS is determined by the change in acceleration of the setpoints. Full article
(This article belongs to the Special Issue Kinematics and Dynamics of Mechanisms and Machines)
Show Figures

Figure 1

Article
3D Reconstruction of High Reflective Welding Surface Based on Binocular Structured Light Stereo Vision
Machines 2022, 10(2), 159; https://doi.org/10.3390/machines10020159 - 20 Feb 2022
Cited by 1 | Viewed by 635
Abstract
The inspection of welding surface quality is an important task for welding work. With the development of product quality inspection technology, automated and machine vision-based inspection have been applied to more industrial application fields because of its non-contact, convenience, and high efficiency. However, [...] Read more.
The inspection of welding surface quality is an important task for welding work. With the development of product quality inspection technology, automated and machine vision-based inspection have been applied to more industrial application fields because of its non-contact, convenience, and high efficiency. However, challenging material and optical phenomena such as high reflective surface areas often present on welding seams tend to produce artifacts such as holes in the reconstructed model using current visual sensors, hence leading to insufficiency or even errors in the inspection result. This paper presents a 3D reconstruction technique for highly reflective welding surfaces based on binocular style structured light stereo vision. The method starts from capturing a fully lit image for identifying highly reflective regions on a welding surface using conventional computer vision models, including gray-scale, binarization, dilation, and erosion. Then, fringe projection profilometry is used to generate point clouds on the interested area. The mapping and alignment from 2D image to 3D point cloud is then established to highlight features that are vital for eliminating “holes”—large featureless areas—caused by high reflections such as the specular mirroring effect. A two-way slicing method is proposed to operate on the refined point cloud, following the concept of dimensionality reduction to project the sliced point cloud onto different image planes before a Smoothing Spline model is applied to fit the discrete point formed by projection. The 3D coordinate values of points in the “hole” region are estimated according to the fitted curves and appended to the original point cloud using iterative algorithms. Experiment results verify that the proposed method can accurately reconstruct a wide range of welding surfaces with significantly improved precision. Full article
(This article belongs to the Special Issue Precision Measurement and Machines)
Show Figures

Figure 1

Article
Precise Measurement and Visual Expression of Gear Overall Deviation
Machines 2022, 10(2), 158; https://doi.org/10.3390/machines10020158 - 20 Feb 2022
Viewed by 297
Abstract
This paper proposes a non-contact measurement, analysis, and visualization method for the overall deviation of gears based on a laser displacement sensor. We implement error compensation and coordinate transformation on the tooth profile data collected by the laser probe through an algorithm, and [...] Read more.
This paper proposes a non-contact measurement, analysis, and visualization method for the overall deviation of gears based on a laser displacement sensor. We implement error compensation and coordinate transformation on the tooth profile data collected by the laser probe through an algorithm, and fit all the data points to the gear surface using a 3 × 3 degree spline function. According to the established actual surface model of the gear, the tooth profile curve on any section of the gear and its various deviations can be obtained. To find the overall deviation on the tooth profile surface, the deviation data is refined and fitted into a curved surface by the Newton difference method. The overall deviation can be represented on the gear surface in the form of a color map, and then the color map of the overall deviation of the gear can be obtained. In addition, it can intuitively analyze the distribution of the overall deviation on the gear surface, and realize the visual expression of the deviation. Finally, through experimental verification, we prove that this method can quickly and accurately analyze the various deviations of the gears and the distribution of the deviation, and can effectively improve the detection accuracy and efficiency of the gears. Full article
(This article belongs to the Special Issue Precision Measurement and Machines)
Show Figures

Figure 1

Article
Modification and Noise Reduction Design of Gear Transmission System of EMU Based on Generalized Regression Neural Network
Machines 2022, 10(2), 157; https://doi.org/10.3390/machines10020157 - 18 Feb 2022
Viewed by 396
Abstract
In view of traction gear vibration and noise affecting the performance of the transmission system and the comfort of passengers when the electric multiple units (EMU) is running at high speed, taking the traction gear transmission system of an EMU as the research [...] Read more.
In view of traction gear vibration and noise affecting the performance of the transmission system and the comfort of passengers when the electric multiple units (EMU) is running at high speed, taking the traction gear transmission system of an EMU as the research object by using Romax software to construct the parametric modification model of the gear transmission system based on gear modification theory. Combined with multibody dynamics, the vibration response characteristics of the transmission system are simulated and analyzed. A radiated noise prediction model is established using the acoustic boundary element method, based on the generalized regression neural network (GRNN). To further explore the influence of gear modification methods and parameters on vibration and noise characteristics and minimize gear transmission’s radiation noise. A particle swarm optimization (PSO) algorithm is designed to solve the optimal modification parameters. The simulation results reveal that after the optimization and modification, the gear transmission error is significantly reduced, the contact status is considerably improved, and the root mean square value of the acoustic power level is reduced by 13.10 dB, which is a reduction of 14%. It shows that the design can effectively reduce the radiation noise of EMU gear trans-mission system. Full article
Show Figures

Figure 1

Article
Predicting the Electrical Impedance of Rolling Bearings Using Machine Learning Methods
Machines 2022, 10(2), 156; https://doi.org/10.3390/machines10020156 - 18 Feb 2022
Cited by 1 | Viewed by 363
Abstract
The present paper describes a measurement setup and a related prediction of the electrical impedance of rolling bearings using machine learning algorithms. The impedance of the rolling bearing is expected to be key in determining the state of health of the bearing, which [...] Read more.
The present paper describes a measurement setup and a related prediction of the electrical impedance of rolling bearings using machine learning algorithms. The impedance of the rolling bearing is expected to be key in determining the state of health of the bearing, which is an essential component in almost all machines. In previous publications, the determination of the impedance of rolling bearings has already been advanced using analytical methods. Despite the improvements in accuracy achieved within the calculations, there are still discrepancies between the calculated and the measured impedance, leading to an approximately constant off-set value. This discrepancy motivates the machine learning approach introduced in this paper. It is shown that with the help of the data-driven methods the difference between analytical prediction and measurement is reduced to the order of up to 2% across the operational range analyzed so far. To introduce the context of the research shown, first the underlying physics of bearing impedance is presented. Subsequently different machine learning approaches are highlighted and compared with each other in terms of their prediction quality in the results part of this paper. As a further aspect, in addition to the prediction of the bearing impedance, it is investigated whether the rotational speed present at the bearing can be predicted from the frequency spectrum of the impedance using order analysis methods which is independent from the force prediction accuracy. The background to this is that, if the prediction quality is sufficiently high, the additional use of speed sensors could be omitted in future investigations. Full article
Show Figures

Graphical abstract

Article
Multi-Sensor Data Driven with PARAFAC-IPSO-PNN for Identification of Mechanical Nonstationary Multi-Fault Mode
Machines 2022, 10(2), 155; https://doi.org/10.3390/machines10020155 - 18 Feb 2022
Cited by 1 | Viewed by 318
Abstract
Data analysis has wide applications in eliminating the irrelevant and redundant components in signals to reveal the important informational characteristics that are required. Conventional methods for multi-dimensional data analysis via the decomposition of time and frequency information that ignore the information in signal [...] Read more.
Data analysis has wide applications in eliminating the irrelevant and redundant components in signals to reveal the important informational characteristics that are required. Conventional methods for multi-dimensional data analysis via the decomposition of time and frequency information that ignore the information in signal space include independent component analysis (ICA) and principal component analysis (PCA). We propose the processing of a signal according to the continuous wavelet transform and the construction of a three-dimensional matrix containing the time–frequency–space information of the signal. The dimensions of the three-dimensional matrix are reduced by parallel factor analysis, and the time characteristic matrix, frequency characteristic matrix, and spatial characteristic matrix are obtained with tensor decomposition. Through the comparative analysis of the simulation and the experiment, the time characteristic matrix and the frequency characteristic matrix can accurately characterize the normal and fault states of the mechanical equipment. On this basis, the authors established a probabilistic neural network classification model optimized by the improved particle swarm algorithm (IPSO). The parallel factor (PARAFAC) decomposition algorithm can extract features from the centrifugal pump experimental data for normal and multiple fault states, establish the mapping relationship of different fault features of the centrifugal pump in time, frequency, and space, and import the fault features into the model classification. The above measures can significantly improve the fault identification rate and accuracy for a centrifugal pump. Full article
Show Figures

Figure 1

Article
Dynamic Analysis of a High-Contact-Ratio Spur Gear System with Localized Spalling and Experimental Validation
Machines 2022, 10(2), 154; https://doi.org/10.3390/machines10020154 - 18 Feb 2022
Viewed by 338
Abstract
The dynamic characteristics and tooth spalling fault features are studied for the high-contact-ratio spur gear bearing system. The bending torsional dynamic model is proposed in this study for the gear bearing system with an ellipsoid spalling fault. This model also considers time-varying meshing [...] Read more.
The dynamic characteristics and tooth spalling fault features are studied for the high-contact-ratio spur gear bearing system. The bending torsional dynamic model is proposed in this study for the gear bearing system with an ellipsoid spalling fault. This model also considers time-varying meshing stiffness, tooth friction, fractal gear backlash, and comprehensive transmission error. The meshing stiffness of the system is evaluated using the potential energy method. The bifurcation diagram, time-domain waveform, Poincaré map, phase map, frequency spectrum, and related three-dimensional map are used as tools to analyze the system’s dynamic response qualitatively. The results reveal that the system’s motion with ellipsoid tooth spalling defect exhibits rich dynamic behavior. The response of the proposed dynamic model is consistent with experimental results in the frequency domain. Therefore, the developed dynamic model can predict the system’s vibration behavior with localized spalling fault. Hence, it could also provide a theoretical foundation for future spall defect diagnosis of the gear transmission system. Full article
Show Figures

Figure 1

Article
Application of a Robust Decision-Making Rule for Comprehensive Assessment of Laser Cutting Conditions and Performance
Machines 2022, 10(2), 153; https://doi.org/10.3390/machines10020153 - 18 Feb 2022
Cited by 2 | Viewed by 331
Abstract
Laser cutting parameters synergistically affect, although in different quantitative and qualitative manners, multiple process performances, such as the resulting cut quality characteristics, material removal rate, cutting time, and costs, and the determination of the most appropriate laser cutting conditions for a given application [...] Read more.
Laser cutting parameters synergistically affect, although in different quantitative and qualitative manners, multiple process performances, such as the resulting cut quality characteristics, material removal rate, cutting time, and costs, and the determination of the most appropriate laser cutting conditions for a given application is of prime importance. Given the existence of multiple mutually opposite performances, assessment and laser cutting conditions and performance can be considered a multiple-criteria decision-making (MCDM) problem. In order to overcome the possible inconsistency of rankings determined by different MCDM methods while solving the same decision-making problem, the present study promotes a novel methodology for the assessment and selection of laser cutting conditions by developing a robust decision-making rule (RDMR) that combines different decision-making rules from six MCDM methods and Taguchi’s principles of robust design. In order to illustrate the application of the proposed methodology, CO2 laser cutting in a stainless-steel experiment, based on the use of the Box–Behnken design, was conducted. On the basis of the experimental results, a comprehensive laser cutting MCDM model was developed with seven criteria related to cut quality (i.e., kerf geometry and cut surface), productivity, variable costs, and environmental aspects. It was observed that there was no laser cutting condition that could be considered as the best regime with respect to the different laser cutting process performances. Kendall’s and Spearman’s rank correlation coefficients indicated a certain level of disagreement among the resulting rankings of the laser cutting conditions produced by the considered MCDM methods, whereas the application of the proposed RDMR ensured the highest level of ranking consistency. Some possibilities for modeling of RDMR and its further use for the assessment of arbitrarily chosen laser cutting conditions and the use of the derived model to perform sensitivity analysis for determining the most influential laser cutting parameters are also discussed and addressed. It was observed that laser cutting parameters in different laser cutting conditions may have a variable effect on the resulting overall process performances. The comparison of the obtained results and the results determined by classical desirability-based multi-objective optimization revealed that there exists substantial agreement between the most preferable and least preferable laser cutting conditions, thus justifying the applied methodology. Full article
(This article belongs to the Special Issue Cutting Tools: Materials, Development and Performance)
Show Figures

Figure 1

Article
Numerical Investigation of Influence of Fluid Rate, Fluid Viscosity, Perforation Angle and NF on HF Re-Orientation in Heterogeneous Rocks Using UDEC T-W Method
Machines 2022, 10(2), 152; https://doi.org/10.3390/machines10020152 - 18 Feb 2022
Cited by 1 | Viewed by 361
Abstract
Numerical simulation is very useful for understanding the hydraulic fracture (HF) re-orientation mechanism from artificial weaknesses. In this paper, the UDEC T-W (Trigon–Weibull distribution) modeling method is adopted to simulate the hydraulic fracturing process in heterogeneous rocks. First, the reliability of this method [...] Read more.
Numerical simulation is very useful for understanding the hydraulic fracture (HF) re-orientation mechanism from artificial weaknesses. In this paper, the UDEC T-W (Trigon–Weibull distribution) modeling method is adopted to simulate the hydraulic fracturing process in heterogeneous rocks. First, the reliability of this method is validated against previous laboratory experiments and numerical simulations. Then the effects of fluid rate, fluid viscosity, perforation angle and natural fracture (NF) on the HF re-orientation process in heterogeneous rocks are studied independently. The results show that the HF re-orientation process depends on the combined effect of these factors. The HF re-orientation distance increases significantly, the final HF re-orientation trajectory becomes more complex and the guiding effect of perforation on the HF propagation path is more evident with the increase of fluid rate, fluid viscosity, and perforation angle if the hydraulic fracturing is performed in relatively heterogeneous rocks, while the differential stress is the main influencing factor and is more likely to dictate the HF propagation path if the rocks become relatively homogeneous. However, increasing the fluid viscosity and fluid rate can attenuate the impact of differential stress and can promote HF propagation along the perforation direction. Besides, NFs are also the important factor affecting HF re-orientation and induce secondary HF re-orientation in some cases in heterogeneous rocks. Full article
(This article belongs to the Special Issue Advances in Fracture Mechanics for Structural Integrity Assessment)
Show Figures

Figure 1

Article
High Temperature Mechanical Properties and Microstructure Evolution of Ti-6Al-4V Alloy Linear Friction Welding Joints
Machines 2022, 10(2), 151; https://doi.org/10.3390/machines10020151 - 18 Feb 2022
Viewed by 393
Abstract
The combination of linear friction welding (LFW) and hot forming processes is limited due to a lack of research on the high-temperature flow behavior and microstructure evolution of welded joints. In this paper, an electric-assisted high-temperature uniaxial tensile test platform based on digital [...] Read more.
The combination of linear friction welding (LFW) and hot forming processes is limited due to a lack of research on the high-temperature flow behavior and microstructure evolution of welded joints. In this paper, an electric-assisted high-temperature uniaxial tensile test platform based on digital image correlation (DIC) is built, and uniaxial tensile tests of Ti-6Al-4V alloy with LFW joints are performed at different temperatures (923–1023 K) and different strain rates (0.001 s−1–0.01 s−1). Then the microstructure of the LFW joints under different hot deformation conditions have been analyzed by scanning electron microscope (SEM), electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM). The results indicate that the high-temperature flow behavior of LFW joints shows an obvious correlation between temperature and strain rate: the yield stress decreases from 203 MPa at 923 K to 105 MPa at 1023 K, and increases from 85 MPa to 130 MPa when the strain rate increases from 0.001 s−1 to 0.01 s−1 at 973 K. The hot deformation mechanisms with deformation conditions have been characterized, which changes from the mechanism of dislocation creep to the mechanism of self-diffusion as the deformation temperature increases from 923 to 1023 K. Especially, the fraction of high angle boundaries (HABs) rapidly rise from 49.2% to 64.1% with the increasing temperatures, the discontinuous dynamic recrystallization (DDRX) become the primary mechanism of nucleation during high-temperature deformation of LFW joints. Full article
(This article belongs to the Section Advanced Manufacturing)
Show Figures

Figure 1

Article
Smart Warehouse Management System: Architecture, Real-Time Implementation and Prototype Design
Machines 2022, 10(2), 150; https://doi.org/10.3390/machines10020150 - 18 Feb 2022
Viewed by 1331
Abstract
The world has witnessed the digital transformation and Industry 4.0 technologies in the past decade. Nevertheless, there is still a lack of automation and digitalization in certain areas of the manufacturing industry; in particular, warehouse automation often has challenges in design and successful [...] Read more.
The world has witnessed the digital transformation and Industry 4.0 technologies in the past decade. Nevertheless, there is still a lack of automation and digitalization in certain areas of the manufacturing industry; in particular, warehouse automation often has challenges in design and successful deployment. The effective management of the warehouse and inventory plays a pivotal role in the supply chain and production. In the literature, different architectures of Warehouse Management Systems (WMSs) and automation techniques have been proposed, but most of those have focused only on particular sections of warehouses and have lacked successful deployment. To achieve the goal of process automation, we propose an Internet-of-Things (IoT)-based architecture for real-time warehouse management by dividing the warehouse into multiple domains. Architecture viewpoints were used to present models based on the context diagram, functional view, and operational view specifically catering to the needs of the stakeholders. In addition, we present a generic IoT-based prototype system that enables efficient data collection and transmission in the proposed architecture. Finally, the developed IoT-based solution was deployed in the warehouse of a textile factory for validation testing, and the results are discussed. A comparison of the key performance parameters such as system resilience, efficiency, and latency rate showed the effectiveness of our proposed IoT-based WMS architecture. Full article
(This article belongs to the Special Issue Intelligent Factory 4.0: Advanced Production and Automation Systems)
Show Figures

Figure 1

Article
The Design Process of an Optimized Road Racing Bicycle Frame
Machines 2022, 10(2), 149; https://doi.org/10.3390/machines10020149 - 18 Feb 2022
Viewed by 502
Abstract
This paper recommends an alternative designing process for a superior road racing bicycle frame manufactured from composite materials that is much faster than typically used design processes. The main design goal is for the rider to be faster under the same riding conditions [...] Read more.
This paper recommends an alternative designing process for a superior road racing bicycle frame manufactured from composite materials that is much faster than typically used design processes. The main design goal is for the rider to be faster under the same riding conditions and with the same effort made. This performance gain is the result of a combined structural and aerodynamic optimization process used during the design process along with the selection of the materials. As the needs of the rider are the focus of this design proposal, the optimization can be carried out only after they are understood. The main difference in this approach compared to the typically used methodology is that, instead of analyzing the frame as a whole from the beginning of the design process and the CFD and CAE iterations, we examine each candidate part of the frame separately. After evaluating the parts’ performances, we select those that performed better to create a single frame. This final frame design is used to choose the appropriate layup that would meet the performance needs of the riders and the necessary safety regulations. The benefit of this approach is that the design time is reduced, allowing the product to reach the market faster. Furthermore, it is more convenient and easier to make any modifications required by marketing or regulations. Full article
(This article belongs to the Special Issue Feature Papers to Celebrate the First Impact Factor of Machines)
Show Figures

Figure 1

Article
Optimal Placement of Sensors Based on Data Fusion for Condition Monitoring of Pulley Group under Speed Variation Condition
Machines 2022, 10(2), 148; https://doi.org/10.3390/machines10020148 - 17 Feb 2022
Viewed by 308
Abstract
Pulley group plays an important role in the transmission of large mechanical equipment. To obtain informative data for condition monitoring, it is very important to optimize sensor placement on the pulley group. However, due to sharp speed fluctuation, heavy load and complex internal [...] Read more.
Pulley group plays an important role in the transmission of large mechanical equipment. To obtain informative data for condition monitoring, it is very important to optimize sensor placement on the pulley group. However, due to sharp speed fluctuation, heavy load and complex internal structure, sensor placement for acquiring optimal monitoring points is still a challenging task. Therefore, a novel sensor optimization method based on data fusion is proposed. In this method, the Kalman filter is firstly used to refine the collected signal for dealing with the variable noises. Subsequently, the variable periodicity strength of the signal is calculated to recognize the non-stationary characteristics of the measured signal. A data fusion technique based on maximum likelihood estimation (MLE) is then introduced to estimate sensitive components from the multi-source sensor signals for finding out optimal sensor placement points. The method is validated experimentally on a test rig of the pulley group with variable speed conditions. Analysis results show that the proposed method can recognize the optimal sensor placement points for the pulley group. Full article
(This article belongs to the Special Issue Advances in Bearing Modeling, Fault Diagnosis, RUL Prediction)
Show Figures

Figure 1

Article
Fixed Abrasive Polishing in an Anhydrous Environment: A Material Removal Model for Fused Silica
Machines 2022, 10(2), 147; https://doi.org/10.3390/machines10020147 - 17 Feb 2022
Viewed by 453
Abstract
Due to the prevalent randomness and uncertainties associated with traditional loose polishing, fixed abrasive polishing in an anhydrous environment has been chosen as a new polishing method. In this paper, cerium oxide is the main component for polishing pellets, and the particle size [...] Read more.
Due to the prevalent randomness and uncertainties associated with traditional loose polishing, fixed abrasive polishing in an anhydrous environment has been chosen as a new polishing method. In this paper, cerium oxide is the main component for polishing pellets, and the particle size distribution of cerium oxide is measured. A material removal model for fixed abrasive polishing of fused silica in an anhydrous environment is proposed. Based on this model, we simulate the roughness of fused silica in fixed abrasive polishing process by using a Monte Carlo method with a constant removal mechanism and obtain the percentage of plastic and chemical removal. The percentage result is then taken into the material removal equation to calculate the material removal rate. The final convergence value of the roughness with 2 μm particle size is about 1.8 nm, while the final convergence value of the surface roughness of the workpiece by Monte Carlo simulation is about 1 nm. The experimental material removal rate at 2 μm particle size is 5.48 μm/h, while the simulation result is 4.29 μm/h. The experiment data of roughness and material removal rate all verify the model. Full article
Show Figures

Figure 1

Article
Improved Wafer Map Inspection Using Attention Mechanism and Cosine Normalization
Machines 2022, 10(2), 146; https://doi.org/10.3390/machines10020146 - 17 Feb 2022
Viewed by 393
Abstract
Wafer map inspection is essential for semiconductor manufacturing quality control and analysis. The deep convolutional neural network (DCNN) is the most effective algorithm in wafer defect pattern analysis. Traditional DCNNs rely heavily on high quality datasets for training. However, obtaining balanced and sufficient [...] Read more.
Wafer map inspection is essential for semiconductor manufacturing quality control and analysis. The deep convolutional neural network (DCNN) is the most effective algorithm in wafer defect pattern analysis. Traditional DCNNs rely heavily on high quality datasets for training. However, obtaining balanced and sufficient labeled data is difficult in practice. This paper reconsiders the causes of the imbalance and proposes a deep learning method that can learn robust knowledge from an imbalanced dataset using the attention mechanism and cosine normalization. We interpret the dataset imbalance as both a feature and a quantity distribution imbalance. To compensate for feature distribution imbalance, we add an improved convolutional attention module to the DCNN to enhance representation. In particular, a feature-map-specific direction mapping module is developed to amplify the positional information of defect clusters. For quantity distribution imbalance, the cosine normalization algorithm is proposed to replace the fully connected layer, and classifier fine-tuning is realized through a small amount of iterative training, which decreases the sensitivity to the quantitative distribution. The experimental results on real-world datasets demonstrate that the proposed method significantly improves the robustness of wafer map inspection and outperforms existing algorithms when trained on imbalanced datasets. Full article
Show Figures

Figure 1

Review
A Review of Key Technologies for High-Speed Motorized Spindles of CNC Machine Tools
Machines 2022, 10(2), 145; https://doi.org/10.3390/machines10020145 - 17 Feb 2022
Viewed by 512
Abstract
The high-speed and high-precision motorized spindle is the future development trend of the CNC machine tool field, and has become the focus of research in the world. High-speed motorized spindles tend to develop in the direction of high precision, high speed, low energy [...] Read more.
The high-speed and high-precision motorized spindle is the future development trend of the CNC machine tool field, and has become the focus of research in the world. High-speed motorized spindles tend to develop in the direction of high precision, high speed, low energy consumption, high efficiency, and high reliability. We undertake a through, systematic review of the development history perspective of the research on precision bearing technology, dynamic balancing technology, thermal error measurement and compensation technology with regard to the key technologies of high-speed motorized spindles. On this basis, the current level of development of key technologies for high-speed motorized spindles is analyzed, and the objective advantages and disadvantages of existing technologies are summarized. Finally, the development tendency of high-speed motorized spindle technology is predicted and foreseen. Full article
Show Figures

Figure 1

Article
General Cutting Load Model for Workload Simulation in Spindle Reliability Test
Machines 2022, 10(2), 144; https://doi.org/10.3390/machines10020144 - 16 Feb 2022
Cited by 1 | Viewed by 558
Abstract
As the key functional component of the machine tool, the reliability test of the spindle is necessary to verify the reliability of the machine tool. In the reliability test, the cutting load model is the guideline of workload simulation and is the prerequisite [...] Read more.
As the key functional component of the machine tool, the reliability test of the spindle is necessary to verify the reliability of the machine tool. In the reliability test, the cutting load model is the guideline of workload simulation and is the prerequisite to ensure the accuracy and effectiveness of the long-term experiment. However, the existing load models usually aim at the specific cutting force at the tool-tip, thereby ignoring the versatility, maneuverability, and accuracy of the load model when applied in the spindle reliability test. In this study, a general cutting load model for the machine tool spindle is established in a form of radial-axial-torque decomposition, and the radial force is simplified as non-rotating status for the maneuverability of conducting a load simulation. The difference between rotating and non-rotating radial force on the reliability calculation is also discussed and corrected using bearing fatigue analysis. A spindle reliability test platform with radial force, axial force, and torque simulation is developed according to the cutting load model, while the loading spectrum is compiled for conducting the spindle reliability test. This research is of great engineering value for the designing of the spindle reliability test. Full article
Show Figures

Figure 1

Article
Stability Analysis of Vaneless Space in High-Head Pump-Turbine under Turbine Mode: Computational Fluid Dynamics Simulation and Particle Imaging Velocimetry Measurement
Machines 2022, 10(2), 143; https://doi.org/10.3390/machines10020143 - 16 Feb 2022
Cited by 1 | Viewed by 449
Abstract
When the Francis-type reversible pump-turbine runs under partial load, the pressure pulsation amplitude and frequency in vaneless space are high, posing a serious threat to the stability of unit operation. Water presents weak compressibility in a high-head pump-turbine, thereby affecting the amplitude–frequency characteristics [...] Read more.
When the Francis-type reversible pump-turbine runs under partial load, the pressure pulsation amplitude and frequency in vaneless space are high, posing a serious threat to the stability of unit operation. Water presents weak compressibility in a high-head pump-turbine, thereby affecting the amplitude–frequency characteristics of pressure pulsation. This study used numerical simulations in a model and prototype pump-turbine and particle image velocimetry (PIV) in a model pump-turbine to examine the internal flow field and pressure pulsation characteristics and determine the effect of the flow in the vaneless space on the amplitude–frequency characteristics of the pressure pulsation. The pressure pulsation amplitude–frequency characteristics were verified through prototype tests. The effects of the weak compressibility of the water on the propagation law of pressure pulsation throughout the flow passage of the prototype and model pump-turbine were roughly similar but exhibited certain differences. Considering the weak compressibility of water, the pressure pulsation fluctuations in each flow passage of the prototype and model pump-turbine exhibit varying degrees of improvement, which is more obvious at the prototype scale. Therefore, the pressure wave disturbance caused by the weak compressibility of the water has different effects on the prototype scale and model scale of the high-head Francis pump-turbine. Full article
(This article belongs to the Section Turbomachinery)
Show Figures

Figure 1

Article
A Twisted and Coiled Polymer Artificial Muscles Driven Soft Crawling Robot Based on Enhanced Antagonistic Configuration
Machines 2022, 10(2), 142; https://doi.org/10.3390/machines10020142 - 16 Feb 2022
Viewed by 545
Abstract
Twisted and coiled polymer (TCP) actuators are becoming increasingly prevalent in soft robotic fields due to their powerful and hysteresis-free stroke, large specific work density, and ease of fabrication. This paper presents a soft crawling robot with spike-inspired robot feet which can deform [...] Read more.
Twisted and coiled polymer (TCP) actuators are becoming increasingly prevalent in soft robotic fields due to their powerful and hysteresis-free stroke, large specific work density, and ease of fabrication. This paper presents a soft crawling robot with spike-inspired robot feet which can deform and crawl like an inchworm. The robot mainly consists of two leaf springs, connection part, robot feet, and two TCP actuators. A system level model of a soft crawling robot is presented for flexible and effective locomotion. Such a model can offer high-efficiency design and flexible locomotion of the crawling robot. Results show that the soft crawling robot can move at a speed of 0.275 mm/s when TCP is powered at 24 V. Full article
(This article belongs to the Section Bioengineering Technology)
Show Figures

Figure 1

Article
Developing Digital Observer of Angular Gaps in Rolling Stand Mechatronic System
Machines 2022, 10(2), 141; https://doi.org/10.3390/machines10020141 - 16 Feb 2022
Viewed by 526
Abstract
Algorithms for monitoring the rolling mill mechatronic system state should be developed on the basis of modern digital technologies. Developing digital shadows (observers) of system state parameters in the periodic measurement mode is promising. This study relevance is defined by frequent emergency breakdowns [...] Read more.
Algorithms for monitoring the rolling mill mechatronic system state should be developed on the basis of modern digital technologies. Developing digital shadows (observers) of system state parameters in the periodic measurement mode is promising. This study relevance is defined by frequent emergency breakdowns of rolling stand mechanical transmissions. Most breakdowns are caused by worn end clutches (heads) of countershafts (spindles) transmitting rotation from the motor to the rolls. This is caused by elastic oscillations due to closing angular gaps when the metal enters the stand. The spindle joint angular gap increases over time with the mill operation. Therefore, it is an important diagnostic parameter that allows for an estimation of the transmission serviceability. In this regard, the problem of monitoring the angular gaps in the rolling stand mechatronic systems is relevant. The paper considers developing an observer of angular gaps in the spindle joints of the ‘electric drive-stand’ mechatronic system of the plate Mill 5000 of Magnitogorsk Iron and Steel Works PJSC (MMK PJSC). The monitored signal (angular gap) is calculated with the mathematical processing of the motor’s physical parameters (speed and electromagnetic torque), measured at a given frequency. The gap is determined indirectly by integrating the speed during its closing. To achieve this, the speed is controlled according to the triangular tachogram at no load. The stand’s electromechanical system modes have been studied using mathematical simulation. The observer’s practical use expediency has been reasoned. The structure of the observer-based angular gap monitoring information system is given. The system has been full-scale tested on Mill 5000, which has confirmed the developed algorithm efficiency. The study’s contribution is a justified and implemented concept of a relatively simple technical solution that can be commercially implemented without extra costs. The angular gap calculation algorithm does not involve complex mathematical techniques and can be implemented in industrial rolling mill controllers. Monitoring is automated without human involvement, which eliminates the human factor. The solution has a specific practical focus and is recommended for implementation at operating rolling mills. Full article
(This article belongs to the Special Issue Mechatronic System for Automatic Control 2022)
Show Figures

Figure 1

Article
Steady-State Fault Detection with Full-Flight Data
Machines 2022, 10(2), 140; https://doi.org/10.3390/machines10020140 - 16 Feb 2022
Viewed by 503
Abstract
Aircraft engine condition monitoring is a key technology for increasing safety and reducing maintenance expenses. Current engine condition monitoring approaches use a minimum of one steady-state snapshot per flight. Whilst being appropriate for trending gradual engine deterioration, snapshots result in a detrimental latency [...] Read more.
Aircraft engine condition monitoring is a key technology for increasing safety and reducing maintenance expenses. Current engine condition monitoring approaches use a minimum of one steady-state snapshot per flight. Whilst being appropriate for trending gradual engine deterioration, snapshots result in a detrimental latency in fault detection. The increased availability of non-mandatory data acquisition hardware in modern airplanes provides so-called full-flight data sampled continuously during flight. These datasets enable the detection of engine faults within one flight by deriving a statistically relevant set of steady-state data points, thus, allowing the application of machine-learning approaches. It is shown that low-pass filtering before steady-state detection significantly increases the success rate in detecting steady-state data points. The application of Principal Component Analysis halves the number of relevant dimensions and provides a coordinate system of principal components retaining most of the variance. Consequently, clusters of data points with and without engine fault can be separated visually and numerically using a One-Class Support Vector Machine. High detection rates are demonstrated for various component faults and even for a minimum instrumentation suite using synthesized datasets derived from full-flight data of commercially operated flights. In addition to the tests conducted with synthesized data, the algorithm is verified based on operational in-flight measurements providing a proof-of-concept. Consequently, the availability of continuously sampled in-flight measurements combined with machine-learning methods allows fault detection within a single flight. Full article
(This article belongs to the Special Issue Diagnostics and Optimization of Gas Turbine)
Show Figures

Figure 1

Article
Influence of Graded Surface Decarburization of Automobile Forging Front Axle on the Bending Behavior Based on a Third-Order Shear Deformation Beam Theory
Machines 2022, 10(2), 139; https://doi.org/10.3390/machines10020139 - 16 Feb 2022
Viewed by 461
Abstract
During the forging process of automobile front axle, the steel near the surface is often decarburized for a certain depth. The mechanical properties at the decarburization layer are graded and different from the inner area, influencing the bending behavior of axles under heavy [...] Read more.
During the forging process of automobile front axle, the steel near the surface is often decarburized for a certain depth. The mechanical properties at the decarburization layer are graded and different from the inner area, influencing the bending behavior of axles under heavy loads. In this paper, the decarburized forging of front axle is regarded as a rectangular thick sandwich beam, composed of a homogeneous core and the functionally graded layer coated on both bottom and top surface. A Third-order Shear Deformation Theory (TSDT) is employed to investigate the static bending behaviors under two point−loads. The properties of sandwich FG material are represented with a piecewise power−law function, and the displacement field governing equations are derived through the virtual work principle. The Navier analytical method and numerical DQM procedures are employed to obtain the bending responses under simply supported boundary conditions, and the results are validated through the comparison with an example in the literature. Then, the transverse deflection, rotation, axial stress, and shear stress are studied in terms of different power−law exponents, decarburization depth, unsymmetrical decarburization depth, unbalance loading, and beam sectional dimension. The study reveals the influence of surface decarburization on the bending behavior of forged automobile front axles, and contributes to the optimization of structure design. Full article
(This article belongs to the Section Machine Design and Theory)
Show Figures

Figure 1

Article
Tool Wear Rate and Surface Integrity Studies in Wire Electric Discharge Machining of NiTiNOL Shape Memory Alloy Using Diffusion Annealed Coated Electrode Materials
Machines 2022, 10(2), 138; https://doi.org/10.3390/machines10020138 - 15 Feb 2022
Viewed by 598
Abstract
Electrode material used in wire electric discharge machining (WEDM/wire EDM) plays a vital role in determining the machined component quality. In particular, when machining hard materials like nickel titanium/NiTi (NiTiNOL) shape memory alloy, the quality of electrode material is important as it may [...] Read more.
Electrode material used in wire electric discharge machining (WEDM/wire EDM) plays a vital role in determining the machined component quality. In particular, when machining hard materials like nickel titanium/NiTi (NiTiNOL) shape memory alloy, the quality of electrode material is important as it may have adverse effects on the surface properties of the alloy. Different electrode materials give different performances, as each electrode material is made up of different conductivity, compositions and tensile strength. Therefore, detailed experimental studies have been carried out to understand the effect of diffusion annealed coated wires (X-type and A-type) on NiTiNOL SMA during the wire EDM process. The tool wear rate and surface roughness responses have been studied for both the electrode materials against different wire EDM variables such as pulse time, pause time, wire feed and spark gap set voltage. The impact of these process parameters on the stated output responses has been analyzed and further surface and subsurface analysis of the machined component has been carried out to understand the impact of diffusion annealed electrode materials during the wire EDM process. The investigation reveals that an A-type diffusion annealed coated wire is found to be most suitable in terms of tool wear rate, surface roughness and surface integrity during machining of NiTiNOL shape memory alloy compared to X-type and traditional brass-based electrode materials. Surface topographical properties were studied using confocal microscopic analysis and scanning electron microscope (SEM) with energy-dispersive spectroscopy (EDS) analysis. The subsurface analysis like microhardness and recast layer thickness was also studied for both the wires against different machining conditions. Full article
(This article belongs to the Special Issue Advances in Tool Life Prediction in Machining)
Show Figures

Figure 1

Article
An MPC-LQR-LPV Controller with Quadratic Stability Conditions for a Nonlinear Half-Car Active Suspension System with Electro-Hydraulic Actuators
Machines 2022, 10(2), 137; https://doi.org/10.3390/machines10020137 - 15 Feb 2022
Cited by 2 | Viewed by 514
Abstract
The active suspension system of a vehicle manipulated using electro-hydraulic actuators is a challenging nonlinear control problem. In this research work, a novel Linear Parameter Varying (LPV) State-Space (SS) model with a fictional input is proposed to represent a nonlinear half-car active suspension [...] Read more.
The active suspension system of a vehicle manipulated using electro-hydraulic actuators is a challenging nonlinear control problem. In this research work, a novel Linear Parameter Varying (LPV) State-Space (SS) model with a fictional input is proposed to represent a nonlinear half-car active suspension system. Four different scheduling parameters are used to embed the nonlinearities of both the suspension and the electro hydraulic actuators to represent its nonlinear behavior. A recursive least squares (RLS) algorithm is used to predict the future behavior of the scheduling parameters along the prediction horizon. A Model Predictive Control-Linear Quadratic Regulator (MPC-LQR) is implemented as the control strategy and, to ensure stability, Quadratic Stability conditions are imposed as Linear Matrix Inequalities (LMI) constraints. Furthermore, the inclusion of attraction sets to overcome the conservative performance imposed by the Quadratic Stability conditions is included, as well as a terminal set were the switching between the MPC and the LQR controller is made. Simulations results for the half-car active suspension model over a typical road disturbance are tested to show the effectiveness of the proposed MPC-LQR-LPV controller with quadratic stability conditions in terms of comfort and road-holding. Full article
(This article belongs to the Special Issue Advanced Control of Industrial Electro-Hydraulic Systems)
Show Figures

Figure 1

Article
Adaptive Adjustment Strategy for Walking Characteristics of Single-Legged Exoskeleton Robots
Machines 2022, 10(2), 134; https://doi.org/10.3390/machines10020134 - 14 Feb 2022
Cited by 2 | Viewed by 539
Abstract
In order to achieve the normal walking of hemiplegic patients, this paper proposes a single-legged exoskeleton robot according to the bionics principle, and presents an adaptive adjustment strategy for walking characteristics. The least square regression analysis is used to fit the angle data [...] Read more.
In order to achieve the normal walking of hemiplegic patients, this paper proposes a single-legged exoskeleton robot according to the bionics principle, and presents an adaptive adjustment strategy for walking characteristics. The least square regression analysis is used to fit the angle data of healthy leg joints by cubic polynomials, and then the parametric design of the fitted curve is carried out to obtain the influence of the user’s stride frequency and stride length on the joint angle, so that the gait of the exoskeleton can be adjusted in real time according to the stride length and stride frequency of the healthy leg to realize normal walking. In order to verify the effectiveness of the adaptive adjustment strategy proposed in this paper, the angle of leg joints under normal gait is collected in advance. In addition, an adult male is chosen as the subject to walk on the horizontal ground wearing the single-legged exoskeleton as the experiment. The experimental results show that the designed exoskeleton is reasonable, and the adaptive adjustment strategy proposed in this paper can make the exoskeleton adapt well and follow the gait of healthy legs to achieve a more natural walking state. Full article
(This article belongs to the Special Issue Recent Applications of Assistive Robots)
Show Figures

Figure 1

Article
Design Framework for Motion Generation of Planar Four-Bar Linkage Considering Clearance Joints and Dynamics Performance
Machines 2022, 10(2), 136; https://doi.org/10.3390/machines10020136 - 13 Feb 2022
Viewed by 531
Abstract
In this paper, we present a novel design framework to connect linkage synthesis with dynamics performance of the linkage. The aim of the design framework is to improve the dynamics performance of the mechanism through linkage design, instead of improving manufacturing accuracy or [...] Read more.
In this paper, we present a novel design framework to connect linkage synthesis with dynamics performance of the linkage. The aim of the design framework is to improve the dynamics performance of the mechanism through linkage design, instead of improving manufacturing accuracy or changing driving strategy. Specifically, the design framework is to complete motion generation of four-bar linkage, considering clearance joints and dynamics performance. The constraint model of motion generation and the dynamics model of four-bar linkage are established, respectively. The coordinates of four joints of four-bar linkage are divided into two parts, one of parts is the parameters to improve the dynamics performance of the linkage and is selected as the optimization variables. The other parts of joint coordinates is to satisfy the kinematics requirements and is obtained by solving constraint equations of motion generation. Through optimization calculation, we can obtain the optimal configuration of the four-bar linkage that achieves specified task positions with high motion accuracy and low wear extent of clearance joint. Finally, a numerical example is proposed to demonstrate the novel design framework. Full article
(This article belongs to the Section Machine Design and Theory)
Show Figures

Figure 1

Article
A Systematic Analysis of Printed Circuit Boards Bending during In-Circuit Tests
Machines 2022, 10(2), 135; https://doi.org/10.3390/machines10020135 - 13 Feb 2022
Viewed by 499
Abstract
When performing In-Circuit Tests (ICTs) of Printed Circuit Boards (PCBs), there are certain phenomena related with strain analysis that must be known in order to obtain stronger and more accurate testing results. During testing, PCBs are often subjected to mechanical bending efforts that [...] Read more.
When performing In-Circuit Tests (ICTs) of Printed Circuit Boards (PCBs), there are certain phenomena related with strain analysis that must be known in order to obtain stronger and more accurate testing results. During testing, PCBs are often subjected to mechanical bending efforts that induce excessive strain. This study focuses on the building of a Finite Elements Analysis (FEA) methodology that prevents excessive bending strain in critical points of a PCB during an ICT. To validate this methodology, a set of experimental tests, matched with a set of FEA, were carried out. Thus, companies, before the development of an ICT machine (fixture), will be able to use this FEA methodology to predict whether the maximum strain of a PCB under study, when subjected to its ICT, will damage it, thus reducing unnecessary production costs. A guideline was thus designed to enable the creation of the most representative Finite Elements Model (FEM) for any PCB, based on its amount and direction of copper traces. Full article
(This article belongs to the Special Issue Feature Papers to Celebrate the First Impact Factor of Machines)
Show Figures

Figure 1

Article
Developing and Implementing a Lean Performance Indicator: Overall Process Effectiveness to Measure the Effectiveness in an Operation Process
Machines 2022, 10(2), 133; https://doi.org/10.3390/machines10020133 - 12 Feb 2022
Viewed by 638
Abstract
The purpose of this paper is to build up and implement a framework of a lean performance indicator with collaborative participation. A new indicator derived from OEE is presented, overall process effectiveness (OPE), which measures the effectiveness of an operation process. The action [...] Read more.
The purpose of this paper is to build up and implement a framework of a lean performance indicator with collaborative participation. A new indicator derived from OEE is presented, overall process effectiveness (OPE), which measures the effectiveness of an operation process. The action research (AR) methodology was used; collaborative work was done between researchers and management team participation. The framework was developed with the researchers’ and practitioners’ experiences, and the data was collected and analyzed; some improvements were applied and finally, a critical reflection of the process was done. This new metric contributes to measuring the unloading process, identifying losses, and generating continuous improvement plans tailored to organizational needs, increasing their market competitiveness and reducing the non-value-add activities. The OEE framework is implemented in a new domain, opening a new line of research applied to logistic process performance. This framework contributes to recording and measuring the data of one unloading area and could be extrapolated to other domains for lean performance. It was possible to generate and validate knowledge applied in the field. This study makes collaborative participation providing an effectiveness indicator that helps the managerial team to make better decisions through AR methodology. Full article
(This article belongs to the Special Issue Lean Manufacturing and Industry 4.0)
Show Figures

Figure 1

Article
Correlation Stability Problem in Selecting Temperature-Sensitive Points of CNC Machine Tools
Machines 2022, 10(2), 132; https://doi.org/10.3390/machines10020132 - 12 Feb 2022
Viewed by 582
Abstract
In the thermal-error compensation of CNC machine tools, temperature-sensitive points (TSPs) are used for predicting thermal error and need to have a high correlation with the thermal error. The stability of the correlation between TSPs and the thermal error is the key to [...] Read more.
In the thermal-error compensation of CNC machine tools, temperature-sensitive points (TSPs) are used for predicting thermal error and need to have a high correlation with the thermal error. The stability of the correlation between TSPs and the thermal error is the key to long-term prediction accuracy. In this paper, the uncertainty-calculation method of the correlation coefficient is proposed to measure the stability of the correlation, and the reasons that affect the stability of the correlation of TSPs are analyzed. Then, the uncertainty-correlation coefficient is proposed, which can comprehensively evaluate the correlation and the stability of the correlation between TSPs and the thermal error. Through long-term experimental verifications, compared with the current TSP selection algorithm, the uncertainty-correlation coefficient can help to select a more stable TSP and improve the long-term prediction accuracy of the thermal error. Full article
Show Figures

Figure 1

Article
Combined Propulsion and Levitation Control for Maglev/Hyperloop Systems Utilizing Asymmetric Double-Sided Linear Induction Motors
Machines 2022, 10(2), 131; https://doi.org/10.3390/machines10020131 - 11 Feb 2022
Viewed by 606
Abstract
This article presents a new method for combined levitation and propulsion control in maglev/Hyperloop systems by selectively applying AC and DC modes of operation to a group of asymmetric double-sided linear induction motors (ADSLIMs). Although adjusting the AC current magnitude of lower and [...] Read more.
This article presents a new method for combined levitation and propulsion control in maglev/Hyperloop systems by selectively applying AC and DC modes of operation to a group of asymmetric double-sided linear induction motors (ADSLIMs). Although adjusting the AC current magnitude of lower and upper primary windings in ADSLIMs allows simultaneous control of thrust and lift forces, the limitation of this current balancing technique prohibits them from producing a high lift force while operating with low thrust force. To overcome this limitation and to simultaneously control the thrust and lift forces of the ADSLIMs with high efficiency under different operating conditions, a combination of AC and DC modes of operation is proposed. AC mode of operation consists of feeding different AC current amplitudes to the upper and lower ADSLIM primary windings to produce and control the required thrust and lift forces. The DC mode of operation consists of controlling one or several ADSLIMs to operate with DC excitation to realize the desired lift force at lower thrusts which otherwise cannot be achieved by operating in AC mode alone. The concept of the new combined control strategy is studied using two-dimensional finite element (FE) electromagnetic simulations and compared with an Inductrack permanent magnet (PM) based passive magnetic levitation system. Full article
(This article belongs to the Special Issue Design and Control of Electrical Machines)
Show Figures

Figure 1

Previous Issue
Next Issue
Back to TopTop