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This manuscript addresses the critical challenges in achieving high-accuracy remote control of electromechanical systems, given their inherent nonlinearities and dynamic complexities. Traditional diagnostics often suffer from data inaccuracies and limitations in analytical techniques. The focus is on enhancing the dynamic model accuracy for remote induction motor control in both closed- and open-loop speed control systems, which is essential for real-time process monitoring. The proposed solution includes real-time measurements of input and output physical quantities to mitigate inaccuracies in traditional diagnostic methods. The manuscript discusses theoretical aspects of nonlinear torque formation in induction drives and introduces a dynamic model employing vector control and speed control schemes alongside standard frequency control methods. These approaches optimize frequency converter settings to enhance system performance under varying nonlinear conditions. Additionally, the manuscript explores methods to analyze dynamic, systematic errors arising from frequency converter inertial properties, thereby improving electromechanical equipment condition diagnostics. By addressing these challenges, the manuscript significantly advances the field, offering a promising future with enhanced dynamic model accuracy, real-time monitoring techniques, and advanced control methods to optimize system reliability and performance. [ABSTRACT FROM AUTHOR]

Conventionally, the electromechanical system requires the installation of auxiliary displacement sensors and only the amount on the drive part and motion end, which increases volume, cost, and measurement error in the system. This paper presents an integrated measurement method with a sensing head, which takes the equal division characteristics of mechanical structures as part of the sensor, thus, the so-called self-sensing system. Moreover, the displacement is measured by counting the time pulses. The sensing head is integrated with the entire electromechanical system, including the driving, transmitting, and moving parts. Thus, the integration of the sensing part is greatly improved. Taking the rotary table as a special example, and the sensing head embedded into each part of the system, displacement information is obtained by the common processing system and fused by the adaptive weighted average method. The results of the experiment show that the fusion precision of each component is higher than only the motor position information as the feedback. The proposed method is a practical self-sensing technology with significant volume reduction and intelligent control benefits in the industry, especially suitable for extremely small and narrow spaces. [ABSTRACT FROM AUTHOR]

A comprehensive mathematical model of a small hydroelectric power plant for a simulation modelling system has been developed. The model consists of the following simulation mathematical models: a hydraulic turbine with an adjustable guide device, its hydraulic network, an electromechanical system, and a reservoir model. These simulation models are based on the differential equations of electrical, mechanical, and hydraulic equilibrium and are designed to determine the values of currents, speeds, and performance of steady-state operating modes, taking into account the nonlinear properties of the equation parameters. To improve the adequacy of the complex model, a refined simulation model of an induction machine with loss detailing was applied and verified to specify the efficiency and permissible heating power in the motor and generator modes. The losses in steel are ac-counted for by their equivalent circuits. The information on the calculated values of the operating mode parameters allows deter-mining the value of the efficiency indicators of the hydroelectric power plant system under different operating conditions, which makes it possible to formulate optimal modes. Based on the results of a series of calculations with varying static head and open-ing of the blades of the axial guide apparatus, the regularities of changes in their optimal ratio according to the criterion of maximum electric power generated per unit of reservoir water flow used in the formation of the power plant's shunting mode were investigated. Based on the information on the value of the natural flow and the characteristics of the turbine unit, a stable level of static head is determined, which ensures the maximum generated electric power. The power plant's shunting mode was studied to determine the impact of changing the number of simultaneously operating units on the amount of electricity generated and changes in its capacity (the possibility of reducing the unevenness of the generated power by almost two times and increasing the minimum capacity by 30% was shown). Compared to the steady-state flow, the shunting mode provides an almost twofold increase in electricity generation and a threefold increase in efficiency, taking into account the differential cost of electricity by time of day. [ABSTRACT FROM AUTHOR]

Summary Belief rule base (BRB) is an effective nonlinear relationship modeling approach. It has been widely used in the fault diagnosis of electromechanical systems. To improve the performance of the BRB‐based diagnostic model, a two‐phase features extraction approach called CNPCA based on complex network (CN) and principal component analysis (PCA) is proposed in this paper. In the first phase, the weighted visibility graph method is applied to transform the time series data of monitored variables into complex networks. Then the statistical attributes of the constructed networks are extracted as the initial features. In the second phase, the PCA method is used to process the initial features and the principal component features are obtained. After that, the CNPCA‐BRB diagnostic model for the electromechanical system is constructed. The experimental results of the elevator fault diagnosis show that the constructed diagnostic model outperforms better than the classical ones. It demonstrates that the CNPCA approach can ensure the integrity of fault information in the features and improve the separability of the fault features. [ABSTRACT FROM AUTHOR]

To realize and handle power consumption details of sustainability, power consumption efficiency measurement for an electromechanical system within a long-term period is critical. Practically, data envelopment analysis (DEA) is useful to measure power consumption efficiency of an electromechanical system for yielding relative efficiencies of peer decision-making units (DMUs). Generally, traditional DEA scarcely considered undesirable outputs, and thus Hwang et al. developed DEA with linear programming to measure DMUs with undesirable outputs. Based on above, inputs, desirable outputs, and undesirable outputs of DMUs in this paper are assumed into triangular fuzzy numbers for grasping data uncertainty and obtaining more messages. Since inputs and outputs of DMUs in Hwang et al.'s were shown by crisp values, DMUs with fuzzy inputs and outputs were unable to be measured. Due to Kao and Liu's fuzzy efficiency measures in DEA, Hwang et al.'s is modified into fuzzy DEA to measure DMUs. In fuzzy DEA, DMUs composed of triangular fuzzy numbers are easily yielded their fuzzy efficiency values and then the efficiency values of fuzzy DMUs are rationally judged by corresponding judgement rules. With fuzzy DEA, efficient DMUs are clearly discriminated from inefficient ones, and then efficient DMUs are evaluated by fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) to find the optimal DMU. According to fuzzy DEA and TOPSIS, the power consumption efficiency of an electromechanical system within a long-term period for sustainability are rationally measured and evaluated. [ABSTRACT FROM AUTHOR]

This paper addresses the challenge of adaptive control for nonstrict-feedback nonlinear systems that involve input delay, actuator faults, and external disturbance. To deal with the complexities arising from input delay and unknown functions, we have incorporated Pade approximation and radial basis function neural networks, respectively. An adaptive controller has been developed by utilizing the Lyapunov stability theorem and the backstepping approach. The suggested method guarantees that the tracking error converges to a compact neighborhood that contains the origin and that every signal in the closed-loop system is semi-globally uniformly ultimately bounded. To demonstrate the efficacy of the proposed method, an electromechanical system application example, and a numerical example are provided. Additionally, comparative analysis was conducted between the Pade approximation proposed in this paper and the auxiliary systems in the existing method. Furthermore, error assessment criteria have been employed to substantiate the effectiveness of the proposed method by comparing it with existing results. [ABSTRACT FROM AUTHOR]

This paper addresses the challenge of adaptive control for nonstrict-feedback nonlinear systems that involve input delay, actuator faults, and external disturbance. To deal with the complexities arising from input delay and unknown functions, we have incorporated Pade approximation and radial basis function neural networks, respectively. An adaptive controller has been developed by utilizing the Lyapunov stability theorem and the backstepping approach. The suggested method guarantees that the tracking error converges to a compact neighborhood that contains the origin and that every signal in the closed-loop system is semi-globally uniformly ultimately bounded. To demonstrate the efficacy of the proposed method, an electromechanical system application example, and a numerical example are provided. Additionally, comparative analysis was conducted between the Pade approximation proposed in this paper and the auxiliary systems in the existing method. Furthermore, error assessment criteria have been employed to substantiate the effectiveness of the proposed method by comparing it with existing results.

Three distinct synchronized switching circuits based on a magnetostrictive actuator are compared in this paper to examine their control mechanisms and circuit characteristics. These circuits include a semi-active shunt circuit, a semi-active current inversion and amplification circuit, and a semi-active automatic current inversion and amplification circuit. Each circuit type employs an additional electronic switch. The synchronized switching method enables the rational control of the circuit current generated by the magnetostrictive actuator to fulfill any desired control strategy. Simulation and experimental results on a 10-bay truss structure reveal that the three circuits can effectively adjust the polarity of the induced current as needed. The three circuits are then compared to thoroughly analyze their unique characteristics and explain their respective advantages and dis-advantages. Using the comparison results, various options available for control circuit design are demonstrated. [ABSTRACT FROM AUTHOR]

The object of research is electromagnetic and mechanical processes in magnetic transmission for an autonomous wind power plant of small power. The use of magnetic transmission as part of an autonomous wind power plant makes it possible to improve the reliability and efficiency of such a system. In the current work, a study of magnetic transmission as part of an autonomous wind power plant was carried out to investigate the parameters and characteristics of magnetic transmission. This paper reports the construction of a numerical simulation mathematical model of a magnetic reducer operating as part of an autonomous wind power plant with a permanent magnet generator. The model takes into account discrete structure of internal and external rotors and modulator; changes in model parameters when input parameters change. It also takes into account losses, change of load angle and electromagnetic moment; the effect of changing the generator load. The built model of the magnetic reducer system differs in that the change in the generator load leads to a shift of the operating point on the mechanical characteristics of the rotor of the wind power plant (WPP). The model also works in the opposite direction: changes in wind parameters affect power, voltage, current, and electromagnetic moment. With the help of the model built, the parameters and characteristics of not only the magnetic reducer but also other components of the system were investigated. The efficiency at the output of the electric generator was determined, which is ≈75 % at a load of 2.0 kW. The magnetic transmission moment at a wind speed of 7.8 m/s for the high-speed rotor is 0.91 N∙m, and the low-speed rotor is 7.8 N∙m, which corresponds to a transmission ratio of 8.6. This expands opportunities for exploratory research. [ABSTRACT FROM AUTHOR]

Compression systems based electromechanical actuators require a good understanding of their dynamics for a better performance. This paper deals with the study of the nonlinear dynamics of an electromechanical system with two rotating arms subjected to a sinusoidal excitation for fluid compression purposes. The physical model integrating two balloons to be compressed by the arms alternately is presented and the mathematical equations traducing their dynamics are established. We emphasize on the influence of some control parameters namely the supply voltage, the discontinuity position and the viscoelastic ratio on the behaviour of the angular displacement of the arms. The study is also done by neglecting the inductance in the electrical part of the system. It is obtained that while the arms exhibit periodic motion during regular movement, compression of the balloons induces a shift to multi-periodic or chaotic dynamics, occasionally reverting to periodicity. Experimental and numerical simulation results demonstrate good agreement, with the R-system approximating more experimental outcomes than the RL-system. These findings hold significant implications for various environmental applications utilizing pump technology.

This manuscript addresses the critical challenges in achieving high-accuracy remote control of electromechanical systems, given their inherent nonlinearities and dynamic complexities. Traditional diagnostics often suffer from data inaccuracies and limitations in analytical techniques. The focus is on enhancing the dynamic model accuracy for remote induction motor control in both closed- and open-loop speed control systems, which is essential for real-time process monitoring. The proposed solution includes real-time measurements of input and output physical quantities to mitigate inaccuracies in traditional diagnostic methods. The manuscript discusses theoretical aspects of nonlinear torque formation in induction drives and introduces a dynamic model employing vector control and speed control schemes alongside standard frequency control methods. These approaches optimize frequency converter settings to enhance system performance under varying nonlinear conditions. Additionally, the manuscript explores methods to analyze dynamic, systematic errors arising from frequency converter inertial properties, thereby improving electromechanical equipment condition diagnostics. By addressing these challenges, the manuscript significantly advances the field, offering a promising future with enhanced dynamic model accuracy, real-time monitoring techniques, and advanced control methods to optimize system reliability and performance.

Conventionally, the electromechanical system requires the installation of auxiliary displacement sensors and only the amount on the drive part and motion end, which increases volume, cost, and measurement error in the system. This paper presents an integrated measurement method with a sensing head, which takes the equal division characteristics of mechanical structures as part of the sensor, thus, the so-called self-sensing system. Moreover, the displacement is measured by counting the time pulses. The sensing head is integrated with the entire electromechanical system, including the driving, transmitting, and moving parts. Thus, the integration of the sensing part is greatly improved. Taking the rotary table as a special example, and the sensing head embedded into each part of the system, displacement information is obtained by the common processing system and fused by the adaptive weighted average method. The results of the experiment show that the fusion precision of each component is higher than only the motor position information as the feedback. The proposed method is a practical self-sensing technology with significant volume reduction and intelligent control benefits in the industry, especially suitable for extremely small and narrow spaces.

This article investigates an adaptive finite time command filtered backstepping control design for a class of uncertain full state constrained strict‐feedback nonlinear systems. The proposed adaptive control strategy is constructed by combining the barrier Lyapunov functions (BLFs), the adaptive command filtered backstepping control method and the finite time control theory. The BLFs are utilized to overcome the violation of the full state constraints. The proposed adaptive control approach is introduced to avoid the problem of the explosion of complexity and the compensating signals are designed to eliminate the influence of the filtering errors caused by the command filters. Moreover, based on the Lyapunov stability theory, it is proved that all the signals of the closed‐loop system are practical finite time stable and the full state constraints are not violated. To verify the efficiency of the proposed adaptive control scheme, simulation results are provided for electromechanical system. [ABSTRACT FROM AUTHOR]

Creating digital twins of industrial equipment requires the development of adequate virtual models, and the calculation of their parameters is a complex scientific and practical problem. To configure and digitally commission automated drives, two-mass electromechanical system models are used. A promising area in which to implement such models is the development of digital shadows, namely drive position observers. Connecting virtual models for online data exchange predetermines the tightening of requirements for their parameter calculation accuracy. Therefore, developing accessible techniques for calculating electromechanical system coordinates is an urgent problem. These parameters are most accurately defined by experiments. The contribution of this paper is the proposition of a method for defining the two-mass system model parameters using the oscillograms obtained in the operating and emergency modes. The method is developed for the horizontal stand drives of a plate mill 5000 and is supported by numerical examples. The technique is universal and comprises calculating the rotating mass inertia torques, elastic stiffness and oscillation damping coefficients, and the time constants of the motor air gap torque control loop. The obtained results have been applied to the development of the elastic torque observer of the rolling stand's electromechanical system. A satisfactory coordinate recovery accuracy has been approved for both open and closed angular gaps in mechanical joints. Recommendations are given for the use of the method in developing process parameter control algorithms based on automated drive position observers. This contributes to the development of the theory and practice of building digital control systems and the implementation of the Industry 4.0 concept in industrial companies. [ABSTRACT FROM AUTHOR]

Three distinct synchronized switching circuits based on a magnetostrictive actuator are compared in this paper to examine their control mechanisms and circuit characteristics. These circuits include a semi-active shunt circuit, a semi-active current inversion and amplification circuit, and a semi-active automatic current inversion and amplification circuit. Each circuit type employs an additional electronic switch. The synchronized switching method enables the rational control of the circuit current generated by the magnetostrictive actuator to fulfill any desired control strategy. Simulation and experimental results on a 10-bay truss structure reveal that the three circuits can effectively adjust the polarity of the induced current as needed. The three circuits are then compared to thoroughly analyze their unique characteristics and explain their respective advantages and dis-advantages. Using the comparison results, various options available for control circuit design are demonstrated.

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The management effectiveness and quality of electromechanical system information management are closely related to the safety production and financial advantages of businesses as it is the core of production management and safety management. This paper develops and establishes the electromechanical system information network from the perspective of electromechanical equipment management and recognizes the significance of parameter optimization in order to actively develop and establish the electromechanical equipment management information system network. Following an analysis of the benefits of the electromechanical equipment management information system network, the equipment management network structure and its connective equipment relationship system are built. Support Vector Machine (SVM) has demonstrated good performance in recent years in the research of electromechanical systems in tackling the classification problem of electromechanical equipment condition monitoring. This paper develops a simulation experiment to evaluate the performance of SVM in processing information from an electromechanical system network, optimizes the SVM's parameters using Particle Swarm Optimization (PSO), and examines the fault signals sent by the electromechanical system network in various time domains. The findings demonstrate that: (1) The SVM-based electromechanical system is capable of analyzing vibration signals by reducing noise, analyzing their frequency spectrum, and analyzing their axis trajectory. (2) The system is capable of identifying undiscovered defects, optimizing the classifier's parameters in accordance with sample characteristics, and assessing the system's efficacy. The main strategies and techniques for establishing company equipment information management are examined in this paper. The network of electromechanical equipment information management system may be built and used to effectively raise the calibre and degree of company equipment management. [ABSTRACT FROM AUTHOR]

The basic electromechanical system of a floating wave power plant has been developed. Besides generating electricity, the power plant protects coastal structure or individual objects in the open sea. The formation of torque at the shaft of the power station is analyzed. The relationship between the capacitance of the energy store and the volume of the reservoir in the energy concentrator is considered. Models of the system components are developed. The relationship between the power of the electromechanical system's components and the rated power of the power station is determined, for the given operating conditions. [ABSTRACT FROM AUTHOR]

In this work, the neural networks-based adaptive fault-tolerant control problem for nonlinear systems with actuator faults and input quantization is investigated. To approximate the nonlinear functions in the control system, radial basis function neural networks (RBFNN) are introduced. Additionally, an adaptive fault-tolerant controller is presented for nonlinear systems to compensate for the effects of input quantization and actuator fault using the backstepping approach and Lyapunov stability theory. It is demonstrated that with the proposed control strategy, all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to an arbitrarily small area of origin. The simulation results of an electromechanical system are shown to verify the validity of the control approach.

Introduction. The article is devoted to the development of the microprocessor automatic control system for a gearless controlled electric drive of a mono-switch tie based on a linear inductor electric motor. This solution provides control the position of the switch point, to carry out the transfer process with a smooth drive of shanks to the frame rail, to protect electric motor elements from overloads. Goal. development and study of the behavior of microprocessor automatic control system for mono-switch tie type with linear inductive electric motor and discrete PID speed controller which coefficients are adjusted according to Chin-Hrons-Reswick method to meet modern traffic safety requirements and improve operational reliability factors. Methodology. On the basis of electric drive theory, a kinematic line of a mono-switch tie type with nonlinear friction characteristic is presented. Using differential equation theory and Laplace transformation, a mathematic description of a linear inductor electric motor has been made. Using the z-transform method, a difference equation for describing a discrete PID speed controller is obtained, the coefficients of which are derived using the Chin-Hrons-Reswick method. A simulation mathematical model of the electric drive mono-switch tie type as the microprocessor automatic control system with linear inductive electric motor and discrete PID speed controller and nonlinear friction characteristic was built in MATLAB. Results. Simulation modelling of a mathematical model of the microprocessor automatic control system of the electric drive mono-switch tie type with the linear inductive electric motor and discrete PID speed controller and nonlinear friction characteristic have been developed and performed. Studies of dynamics of switch point movement have shown that, a drive time of less than 0.7 s at a constant speed motor armature of 0.2 and 0.3 m/s provides to meet modern requirements for railway switch points. The application of discrete PID speed controller has shown improved dynamics of switch point. Originality. First for the electric drive of the mono-switch tie type with linear inductive electric motor a mathematical model of the discrete PID speed controller and nonlinear friction characteristic as an object of speed control of switch point movement, has been developed. Practical value. Mathematical model of a railway track switch of the mono-switch tie type with linear inductive electric motor and discrete PID speed controller has been developed to carry out the control of the position of the switch point, process with a smooth drive them to the frame rail, to protect electric motor elements from overloads.

In this work, the problem of adaptive neural control for nonlinear systems with input nonlinearities and sensor fault in non-strict feedback form is addressed. Input saturation and dead-zone exist in the nonlinear system simultaneously. The impact of external disturbances and sensor fault in nonlinear systems is considered. To approximate the unknown functions in the system, radial basis function neural networks are used. An adaptive neural controller is developed by using the approximation ability of the neural networks and the backstepping method. Based on Lyapunov stability theory, the proposed control method ensures that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and that the output of the system follows the reference signal within a bounded error. Finally, to demonstrate the effectiveness of the proposed control method, one numerical example and a real-life example about an electromechanical system are provided. [ABSTRACT FROM AUTHOR]

This paper considers the experimental and numerical study of an electromechanical arm powered by a DC motor and subjected to the action of permanent magnets. The magnetic torques arise from permanent magnets mounted at the free end of the arm and along a circle. The electrical subsystem is powered by two forms of input signal (DC and AC voltage sources). For each case, we determine the condition for complete rotation of the mechanical arm versus the parameters of the system such as the arm length, the number of magnets, and the frequency of the external signal. The nonlinear dynamics of the system is examined by means of time-histories, bifurcation diagrams, Lyapunov exponents and phase portraits. Chaotic and periodic dynamics are detected numerically and confirmed experimentally. [ABSTRACT FROM AUTHOR]

Copyright of Renewable Energy / Vidnovluvana Energetyka is the property of Institute of Renewable Energy of NAS of Ukraine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper presents research findings in the modelling and optimization of dynamic parameters of mechatronic systems with an induction motor. A mathematical model was developed to analyze currents in dynamic states of squirrel-cage rotors in the case of a line-to-line fault. The findings were verified experimentally using calculations for a 1.5 kW three-phase induction motor. The equations for a stationary 0x, 0y coordinate system relating to the stator were derived. The set of design variables selected in the optimization process contained parameters describing design features of the gear shafts and control units settings. [ABSTRACT FROM AUTHOR]

In European industry, such as metallurgical, mining and processing, construction, food, and chemical, vibration exciters are used, which indicates their wide and, in some cases, unique technological capabilities. The most common are electromagnetic and unbalanced vibration exciters. The advantages of electromagnetic vibration exciters include the ability to control the amplitude of the vibration by changing the electrical power supplied; the disadvantages are high material consumption. However, unbalanced vibration exciters have low energy efficiency, which is associated with difficult start-up conditions and with an overestimated mechanical power of the vibration exciter in relation to the power required by the technology itself, which is due to the need to minimize the effect of the technological load on the operating mode of the vibrating unit. Adjusting the amplitude of the disturbing force of unbalanced vibration exciters, regardless of the vibration frequency, will make it possible to reduce the installed power of the unit by passing the resonant frequency with a minimum disturbing force and compensating for the effect of the process load by means of a closed-loop electric drive. In the course of the study, an analytical description of the interaction of the rotating unbalances located on a common movable platform was obtained. On the basis of these analytical dependencies, a mathematical model was developed that takes into account the dynamic characteristics of a frequency-controlled asynchronous electric drive of a closed-loop control system for the mutual arrangement of rotating unbalances. The simulation results confirmed the possibility of using the specified electric drive to control the oscillation amplitude directly in the process of operation of a four-unbalanced vibration exciter. A physical experiment was carried out to determine the transient processes of changing the angular velocity of an induction motor with an abrupt change in the frequency converter setting. On the basis of this experiment, the previously created mathematical model was refined in terms of describing the dynamic parameters of the electric drive. The proposed structure of the control system, the performance of which has been confirmed by mathematical modeling, makes it possible to implement an adjustable four-unbalanced vibration exciter using single commercially available asynchronous vibrators. [ABSTRACT FROM AUTHOR]

The strategic initiative aimed at building "digital metallurgy" implies the introduction of diagnostic monitoring systems to trace the technical condition of critical production units. This problem is relevant for rolling mills, which provide the output and determine the quality of products of metallurgical companies. Making up monitoring systems requires the development of digital shadows and coordinate observers, the direct measurement of which is either impossible or associated with numerous difficulties. These coordinates include the spindle torque applied by the spring-transmitting torque from the motor to the rolling stand rolls. The development and research are conducted by the example of the electromechanical systems of the horizontal stand at the plate mill 5000. The stand electric drive characteristics are given, and the emergency modes that cause mechanical equipment breakdowns are analyzed that. The relevance of analyzing transient torque processes in emergency modes has been accentuated. The paper points to the shortcomings of the system for elastic torque direct measurement, including low durability due to the harsh operating conditions of precision sensors. It also highlights the need to install the measuring equipment after each spindle. The disadvantage of the previously developed observer is the function of calculating the electric drive speed derivative. This causes a decrease in noise immunity and signal recovery accuracy. The contribution of this paper is building a digital elastic torque observer that has advantages over conventional technical solutions, based on the theoretical and experimental studies. The technique for virtual observer adjustment was developed and tested in the Matlab-Simulink software package. For the first time, a comprehensive analysis was conducted for spindle elastic torques in emergency modes that caused equipment damage. An algorithm was developed for an emergency shutdown of a stand electric drive in the worst-case mode of strip retraction between work and backup rolls, due to the overlap of the strip on the roll. Further, the algorithm was tested experimentally. The criteria for diagnosing pre-emergencies was then justified. An adaptive motor-braking rate controller was developed. The developed observer and emergency braking system are in operation at the mill 5000. Long experimental research proved the efficiency of dynamic load monitoring and the reduction in the number of equipment breakdowns. [ABSTRACT FROM AUTHOR]

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Predictive Maintenance (PM) is a major part of smart manufacturing in the fourth industrial revolution. The classical fault diagnosis approach for complex systems such as an electromechanical system is not effective. Taking the advantage of the successful implementations of PM together with Deep Learning (DL) methods replaces the conventional diagnosis methods with modern diagnosis methods. This study intends to aid experts, engineers, and technicians in different electromechanical systems in comprehending how the PM used DL methods to find the multi-fault diagnosis. In this direction, this paper presents a comprehensive review of recent works of DL techniques that are applied to PM for electromechanical systems by classifying the research according to equipment, fault, parameters, and method. To perform the review, 30 papers that are published in proceedings and journals are reviewed within a time window between the years 2016 to 2022. In the context of the electromechanical system, it is observed that motors are the most equipment selected for PM. Moreover, stator winding faults are found to be less selected than bearing for diagnosis of the unhealthy status of the motor. In terms of DL methods, the study reveals that AE, LSTM, and CNN are mostly used. In addition, poorly mixed models of DL methods are also noticed. Finally, finding the optimal design variable of the DL architecture was not widely explored. [ABSTRACT FROM AUTHOR]

Creating digital twins of industrial equipment requires the development of adequate virtual models, and the calculation of their parameters is a complex scientific and practical problem. To configure and digitally commission automated drives, two-mass electromechanical system models are used. A promising area in which to implement such models is the development of digital shadows, namely drive position observers. Connecting virtual models for online data exchange predetermines the tightening of requirements for their parameter calculation accuracy. Therefore, developing accessible techniques for calculating electromechanical system coordinates is an urgent problem. These parameters are most accurately defined by experiments. The contribution of this paper is the proposition of a method for defining the two-mass system model parameters using the oscillograms obtained in the operating and emergency modes. The method is developed for the horizontal stand drives of a plate mill 5000 and is supported by numerical examples. The technique is universal and comprises calculating the rotating mass inertia torques, elastic stiffness and oscillation damping coefficients, and the time constants of the motor air gap torque control loop. The obtained results have been applied to the development of the elastic torque observer of the rolling stand’s electromechanical system. A satisfactory coordinate recovery accuracy has been approved for both open and closed angular gaps in mechanical joints. Recommendations are given for the use of the method in developing process parameter control algorithms based on automated drive position observers. This contributes to the development of the theory and practice of building digital control systems and the implementation of the Industry 4.0 concept in industrial companies.

Summary: The mechanical antenna (MA) is a new type of low-frequency (LF) transmitting antenna that generates an alternating electromagnetic (EM) signal through the mechanical movement of electric charges or magnetic dipoles, which is an interdisciplinary field including not only antennas but also electromagnetics, materials science, and dynamics. This principle of signaling makes it possible to break the constraints on physical dimensions decided by the wavelength of the traditional antenna so as to achieve LF communications with a smaller size and to provide a novel solution for long-range, underwater, and underground communications, navigation over the horizon, and geological exploring. Therefore, MA has become a research hotspot in the field of LF communications in recent 5 years, and this work proposed a survey on this topic of MA applied for LF transmitting. Firstly, we briefly review traditional low-frequency transmitting antennas and summarize the defect; then we introduce research progress of different implementation schemes for MA, comparing the signaling performance, advantages, and disadvantages of each scheme. Furthermore, we discuss the experiment setup, results, and related technology for MA including signal modulation methods. Finally, we explore prospects for future research about MA. This work presents a comprehensive and critical survey of small LF transmitters based on MA to help the readers to understand and identify the background, status, and challenges of research in this field.

Summary: This article presents a robust adaptive dynamic surface control using σ‐modification adaptation laws for a class of single‐input and single‐output (SISO) uncertain nonlinear systems in strict‐feedback form with parametric uncertainties and external disturbances. The proposed scheme is developed by employing dynamic surface control based robust adaptive control technique. The key features of the approach are that, first, the problem of explosion of complexity inherent in the conventional adaptive backstepping control method is avoided, second, the proposed approach of σ‐modification adaptation laws gives fast and accurate parameter estimation performance, and, third, the closed‐loop signals of the system are proven to be uniformly ultimately bounded (UUB) by using the Lyapunov stability theory. We show the effectiveness of our approach by simulating an electromechanical system. [ABSTRACT FROM AUTHOR]

Introduction. The article is devoted to the development of the microprocessor automatic control system for a gearless controlled electric drive of a mono-switch tie based on a linear inductor electric motor. This solution provides control the position of the switch point, to carry out the transfer process with a smooth drive of shanks to the frame rail, to protect electric motor elements from overloads. Goal. Development and study of the behavior of microprocessor automatic control system for mono-switch tie type with linear inductive electric motor and discrete PID speed controller which coefficients are adjusted according to Chien-Hrones-Reswick method to meet modern traffic safety requirements and improve operational reliability factors. Methodology. On the basis of electric drive theory, a kinematic line of a mono-switch tie type with nonlinear friction characteristic is presented. Using differential equation theory and Laplace transformation, a mathematic description of a linear inductor electric motor has been made. Using the z-transform method, a difference equation for describing a discrete PID speed controller is obtained, the coefficients of which are derived using the Chien-Hrones-Reswick method. A simulation mathematical model of the electric drive mono-switch tie type as the microprocessor automatic control system with linear inductive electric motor and discrete PID speed controller and nonlinear friction characteristic was built in MATLAB. Results. Simulation modelling of a mathematical model of the microprocessor automatic control system of the electric drive mono-switch tie type with the linear inductive electric motor and discrete PID speed controller and nonlinear friction characteristic have been developed and performed. Studies of dynamics of switch point movement have shown that, a drive time of less than 0.7 s at a constant speed motor armature of 0.2 and 0.3 m/s provides to meet modern requirements for railway switch points. The application of discrete PID speed controller has shown improved dynamics of switch point. Originality. First for the electric drive of the mono-switch tie type with linear inductive electric motor a mathematical model of the discrete PID speed controller and nonlinear friction characteristic as an object of speed control of switch point movement, has been developed. Practical value. Mathematical model of a railway track switch of the mono-switch tie type with linear inductive electric motor and discrete PID speed controller has been developed to carry out the control of the position of the switch point, process with a smooth drive them to the frame rail, to protect electric motor elements from overloads. [ABSTRACT FROM AUTHOR]

Obtaining powered linear movement over a long range of motion is a common yet challenging task, as the majority of linear actuators have limited ranges of motion as determined by their functioning mechanisms. In this paper, the authors present a novel belt-based self-actuated linear drive (B-SALD), in which a self-powered moving platform slides on a slotted track with essentially unlimited range of motion (only limited by the length of the track). Unlike the traditional rack-and-pinion mechanism, the B-SALD system uses a double-sided timing belt as the power-transmitting element. With the teeth on its inner surface, the belt interacts with a timing pulley for its own circulation; with the teeth on its outer surface, the belt interacts with a linear rail with parallel slots and drives the translation of the moving platform. The unique functioning mechanism generates multiple distinct advantages: no lubrication is required; the slotted track is simple and inexpensive to manufacture; and it provides an inherent compliance to buffer shock loading. With the experiments conducted on a preliminary prototype, it has been demonstrated that the B-SALD is able to provide accurate positioning and continuous motion control, an overall mechanical efficiency of 70% over the majority of the load range, and the capability of generating large force output in the desired manner. [ABSTRACT FROM AUTHOR]

The present article evaluates the design, analysis, and implementation of a novel fractional second-order sliding mode control scheme for an uncertain second-order system. The developed controller comprises a fractional-order proportional integral derivative sliding surface. The closed-loop stability analysis is performed by using the Lyapunov theorem. The proposed equivalent and switching control signals have been mathematically evaluated at various scenarios comprising uncertainties and disturbances. Several simulations are investigated by including model uncertainties, measurement noises, and disturbances. In addition, various real-time experiments are conducted with different operating conditions. To this end, a real-time reduced-order approximated model of an electromechanical system is constructed. The controller performance has been compared with a number of control techniques to illustrate the promising features of the proposed fractional-order controller. It can be reported that the transient response of the system, control signals applicability, and disturbance rejection capability are quite satisfactory when compared to recently presented control schemes. As a consequence, it is evident that the control scheme has the ability to reduce the chattering phenomenon and increase the system’s robustness.

In this paper, an adaptive dynamic PID sliding surface-based second-order fault-tolerant sliding mode controller for speed control of an electromechanical system is proposed. The paper aims to show how to utilise the robust properties of second-order adaptive dynamic sliding mode control on the problem of structural damage fault. Structural damage fault is apparently studied less than faults of actuator and sensor. Because of this reason, this study focuses on the structural damage fault. In order to solve the chattering which is the main problem of first-order/ traditional SMC, second-order controller is designed. The Lyapunov theorem is used for affirming the design and stability of the closed-loop system. Experimental results show that the control system with the proposed controller is easily implemented. Also, the proposed fault-tolerant controller, concerning parametric uncertainties and disturbances, acquire suitable tracking performance and shows more robustness than the traditional SMC. [ABSTRACT FROM AUTHOR]

Purpose: This study presents the diagnosis of combined or multiple mechanical and electrical faults in an electromechanical system based on support vector machine (SVM). Methods: Time and continuous wavelet transform (CWT)-based features have been extracted from vibration and current signals acquired from ten combined fault conditions from an experimental test rig. Then, SVM algorithm based methodology has been developed for diagnosis the fault conditions. Results: Results show that the combination of vibration and current signal improves the performance of the diagnosis especially at high-load condition in comparison to vibration or current signal alone. The diagnosis is found to be effective with both time domain and CWT features; however, it is slightly better with the CWT features in comparison to time domain-based features. Conclusion: The performance of the diagnosis is found to be better at higher load with both time domain and CWT features. Moreover, the present methodology does not perform well with ramp-up speed conditions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Attractor based performance and reliability modeling of EMSs are proposed. • Physical relationship between EMS reliability and design parameters is constructed. • Attractor based reliability models can be quickly transferred to multi-type EMSs. • Collinear phenomena on the Poincaré section during BLDCM degradation is discovered. • A universal framework of performance and reliability modeling of EMSs is provided. Electromechanical systems (EMS) possess multi-type, fast-iteration, and customized characteristics in modern industry and are usually required for high reliability. To meet the reliability requirements of EMSs, it is essential to identify the physical relationship between the design parameters and reliability of EMSs, i.e., the physical reduction and holistic ability of reliability. However, current reliability models based on physical principles are costly and highly specific, making them lose the transferability to other EMSs and resulting in high computational and time costs when applied to multi-type EMSs. Nevertheless, current reliability models with transferability often lack clear physical reduction and holistic ability, which limits their ability to elucidate the reliability mechanisms in EMSs. Motivated by the above issue, an attractor based performance characterization and reliability evolution modeling method for EMSs is proposed. Firstly, we construct operational state equations of EMSs based on physical principles, discover the attractor as a universal characteristic in EMS operational states, and conduct attractor modeling to characterize EMS performance under constant and periodic external forces. Then, the attractor based reliability evolution modeling is conducted, including attractor based margin, degradation, and measurement equations of EMSs. Two typical EMSs including BLDCMs and resonant circuits are used for the case study, and their attractor based reliability equations physically related to the physical properties, functional thresholds, degradation, and uncertainties are established, revealing the combination of the physical reduction and holistic ability with the transferability of reliability. This work also provides a universal framework for EMS reliability modeling and is conducive to exploring the universality of EMS reliability. [ABSTRACT FROM AUTHOR]