Model Of Electromechanical System Research Articles

МАТЕМАТИЧНЕ МОДЕЛЮВАННЯ ЕЛЕКТРОМЕХАНІЧНОЇ СИСТЕМИ ПЕЧІ ШВИДКІСНОГО НАГРІВУ ПІД ЧАС ДЕМОНТАЖУ ВЕЛИКОГАБАРИТНИХ СКЛАДЕНИХ ВАЛКІВ

МАТЕМАТИЧНЕ МОДЕЛЮВАННЯ ЕЛЕКТРОМЕХАНІЧНОЇ СИСТЕМИ ПЕЧІ ШВИДКІСНОГО НАГРІВУ ПІД ЧАС ДЕМОНТАЖУ ВЕЛИКОГАБАРИТНИХ СКЛАДЕНИХ ВАЛКІВ

On the Port-Hamiltonian Models of some Electrochemical Processes

Electrochemical processes play an important role in many natural and technological processes; such as, mineral refining, water purification, energy storage and generation. The port-Hamiltonian framework has been widely used for modeling and control design of mechanical and electro-mechanical systems. It has demonstrated to be an important tool to analyze and integrate models of different domains. This work discusses the modeling of isothermal electrochemical processes as port-Hamiltonian systems. Port-Hamiltonian models based on the Gibbs energy function are derived for two examples. They illustrate the main steps to obtain a port-Hamiltonian representation from molar and charge balance equations. Further work will consider non isothermal reactions and the analysis of system considering also diffusion phenomena.

Reliability Modeling of Electromechanical System with Meta-Action Chain Methodology

To establish a more flexible and accurate reliability model, the reliability modeling and solving algorithm based on the meta-action chain thought are used in this thesis. Instead of estimating the reliability of the whole system only in the standard operating mode, this dissertation adopts the structure chain and the operating action chain for the system reliability modeling. The failure information and structure information for each component are integrated into the model to overcome the given factors applied in the traditional modeling. In the industrial application, there may be different operating modes for a multicomponent system. The meta-action chain methodology can estimate the system reliability under different operating modes by modeling the components with varieties of failure sensitivities. This approach has been identified by computing some electromechanical system cases. The results indicate that the process could improve the system reliability estimation. It is an effective tool to solve the reliability estimation problem in the system under various operating modes.

Modeling and simulation study of a novel electromechanical clutch actuation system

A novel motor-driven clutch actuator with force-aided lever has been recently developed. A unique spring is used to assist apply of the clutch that can effectively reduce the motor power requirement, and the actuation system can save power consumption during clutch operations with faster response and higher control precision. In this article, a mathematical model of the conceptual clutch actuation system is developed to study the dynamic behavior of the actuator system via computer simulation. The actuator model is further integrated into a dual-clutch transmission and driveline system to demonstrate the effectiveness of the concept in shifting control. The simulation result demonstrates the smooth and fast clutch-to-clutch gear shift and hence validates the feasibility of this new force-aided lever actuation system.

Dynamic characteristics of motor-gear system under load saltations and voltage transients

Abstract In this paper, a dynamic model of a motor-gear system is proposed. The model combines a nonlinear permeance network model (PNM) of a squirrel-cage induction motor and a coupled lateral-torsional dynamic model of a planetary geared rotor system. The external excitations including voltage transients and load saltations, as well as the internal excitations such as spatial effects, magnetic circuits topology and material nonlinearity in the motor, and time-varying mesh stiffness and damping in the planetary gear system are considered in the proposed model. Then, the simulation results are compared with those predicted by the electromechanical model containing a dynamic motor model with constant inductances. The comparison showed that the electromechanical system model with the PNM motor model yields more reasonable results than the electromechanical system model with the lumped-parameter electric machine. It is observed that electromechanical coupling effect can induce additional and severe gear vibrations. In addition, the external conditions, especially the voltage transients, will dramatically affect the dynamic characteristics of the electromechanical system. Finally, some suggestions are offered based on this analysis for improving the performance and reliability of the electromechanical system.

Interaction analysis–based information modeling of complex electromechanical systems in the processing industry

Information modeling for complex electromechanical systems in the processing industry is the foundation for system vulnerability analysis, failure propagation mechanism, and fault root cause tracin...

Study of Piezoelectric Vibration Energy Harvester with non-linear conditioning circuit using an integrated model

ABSTRACTPiezoelectric vibration energy harvester (PVEH) consists of a cantilever bimorph with piezoelectric layers pasted on its top and bottom, which can harvest power from vibrations and feed to low power wireless sensor nodes through some power conditioning circuit. In this paper, a non-linear conditioning circuit, consisting of a full-bridge rectifier followed by a buck–boost converter, is employed to investigate the issues of electrical side of the energy harvesting system. An integrated mathematical model of complete electromechanical system has been developed. Previously, researchers have studied PVEH with sophisticated piezo-beam models but employed simplistic linear circuits, such as resistor, as electrical load. In contrast, other researchers have worked on more complex non-linear circuits but with over-simplified piezo-beam models. Such models neglect different aspects of the system which result from complex interactions of its electrical and mechanical subsystems. In this work, authors have integrated the distributed parameter-based model of piezo-beam presented in literature with a real world non-linear electrical load. Then, the developed integrated model is employed to analyse the stability of complete energy harvesting system. This work provides a more realistic and useful electromechanical model having realistic non-linear electrical load unlike the simplistic linear circuit elements employed by many researchers.

Iterative learning fault diagnosis algorithm for non-uniform sampling hybrid system

For a class of non-uniform output sampling hybrid system with actuator faults and bounded disturbances, an iterative learning fault diagnosis algorithm is proposed. Firstly, in order to measure the impact of fault on system between every consecutive output sampling instants, the actual fault function is transformed to obtain an equivalent fault model by using the integral mean value theorem, then the non-uniform sampling hybrid system is converted to continuous systems with timevarying delay based on the output delay method. Afterwards, an observer-based fault diagnosis filter with virtual fault is designed to estimate the equivalent fault, and the iterative learning regulation algorithm is chosen to update the virtual fault repeatedly to make it approximate the actual equivalent fault after some iterative learning trials, so the algorithm can detect and estimate the system faults adaptively. Simulation results of an electro-mechanical control system model with different types of faults illustrate the feasibility and effectiveness of this algorithm.

An improved PZT cantilever SPICE model for practical energy harvesting circuits simulations and measurements

Energy harvesting, converting ambient energy into electrical energy, represents an alternative to power sensor nodes. The development of piezoelectric energy harvesting systems needs accurate models for system-performance evaluation. Mechanical researchers build distributed models for energy scavengers, simplifying the energy harvesting circuit and using analytical derivation, while electrical researchers focus on the modeling of the energy harvesting circuit and simplifying the structural conditions of the scavenging devices. The challenges for accurate modeling of such electro-mechanical systems remain, when complicated mechanical conditions and practical energy harvesting circuits are considered in system design. This article addresses the above-mentioned problem, employing an equivalent circuit, which bridges the structural modeling and electrical functionality, allowing simulations of complex circuitry. The equivalent circuit has been simulated using SPICE software. Measurements are performed for verification of the proposed model.

Ultimate uniform bounded-stability of inertial coupling electromechanical system via nonlinear time-varying feedback

ABSTRACTThis paper concerns with the problem of stabilisation of inertial coupling electromechanical system. The concept of inertial coupling electromechanical system is an interesting topic from the control theory point of view and its universe of applications. This is because, for stabilisation proposes, the complete model of electromechanical system significantly reduces higher frequency functions in their dynamics caused by high gain controllers. Here, the system stabilisation is achieved by applying nonlinear time-varying controllers. The reason to use a time-varying controller is to give some learning or adaptation in the control process. Moreover, to get a good result for the closed-loop system, the structure of a storage function is based on the classical quadratic function in addition to quadratic function of system total energy. So, the main goal of this paper is obtain a controller that guarantees that the system state error arrives near the required equilibrium in exponential form. Hence, the Ultimate Uniform Bounded-Stability of the system trajectories of desired equilibrium is concluded. Finally, experimental results of the control algorithm developed in this paper are presented briefly.

Wave propagation analysis of embedded (coupled) functionally graded nanotubes conveying fluid

In this study, wave propagation in embedded nanotubes conveying fluid is studied. Tubes are formulated as a functionally graded beam in which material properties are changing in the thickness direction. Dispersion relations are obtained for different material properties, elastic medium stiffness and flow velocities. The effect of flow directions is also investigated. Obtained results can be used in the modeling of nano electromechanical systems.

Bifurcation and chaos analysis of a nonlinear electromechanical coupling transmission system driven by AC asynchronous motor

Considering the torsional vibration in transmission system driven by AC asynchronous motor, this paper proposes a dynamical model of nonlinear electromechanical coupling system by using the energy method. The effect of electromagnetic factors on nonlinear dynamic performance of the electromechanical coupling system is investigated. Firstly, the static bifurcation characteristic under the non-autonomous condition is studied based on the singularity theory of nonlinear system. Secondly, the Hopf bifurcation point and the direction of bifurcation are determined based on the Hopf bifurcation theory. Finally, the bifurcation diagram, Poincare map and the largest Lyapunov exponent are given, which show the influence of electromagnetic stiffness and electromagnetic damping on the chaotic motions of the system.

Математическая модель электромеханической системы колебательного движения с упругими связями

Математическая модель электромеханической системы колебательного движения с упругими связями

Mechanical passive logic module

Nothing from nothing gives simple simile, but something from nothing is an interesting and challenging task. Adolf Lohmann once proposed ‘do nothing machine’ in optics, which only copies input to output. Passive logic module (PALM) is a special type of ‘do nothing machine’ which can converts inputs into one of 16 possible binary outputs. This logic module is not like the conventional irreversible one. It is a simple type of reversible Turing machine. In this manuscript we discussed and demonstrated PALM using mechanical movement of plane mirrors. Also we discussed the theoretical model of micro electro mechanical system (MEMS) based PALM in this manuscript. It may have several valuable properties such as passive operation (no need for nonlinear elements as other logic device require) and modular logic (one device implementing any Boolean logic function with simple internal changes). The result is obtained from the demonstration by only looking up the output. No calculation is required to get the result. Not only that, PALM is a simple type of the famous ‘billiard ball machine’, which also discussed in this manuscript.

Genetic Algorithm-Based Parameters Optimization for the PID Controller Applied in Heave Compensation System

To reduce the negative impact of the unexpected motion in the heave direction when hoisting on the sea, a heave compensation system is indispensable for a floating crane. In this paper, a genetic algorithm-based PID controller is presented to improve the dynamic performance of the heave compensation system. A simulation model of electro-mechanical and hydraulic integrated system of the heave compensation system is built. The simulation results show that the genetic algorithm-based PID control system improves the dynamic characteristics, strengthens the stability and rapidity of the system and even ensures the control effect of the heave compensation system.

Analysis and Research on Modeling Methods of Mems Coupling Dynamic System of Ultrasonic Motor

The ultrasonic motor is a complex dynamic system, which be divided into an electro-mechanical coupling system and a drive and control system. The core of the electro-mechanical coupling system lies in excitation of elliptical movement of the mass points on the surface of the stator and frictional transfer of the power and the movement. Modeling of the electro-mechanical coupling dynamic system of the ultrasonic motor substantially comprises two aspects. First, the dynamic system is viewed as an integral transfer function, and an intuitive relationship between input of the electric energy and output of the power is established. Second, geometric parameters and material parameters of mechanisms are closely correlated with dynamics of the mechanisms.

Relevance of magnetic behavior in the modeling of electro-mechanical systems

The present paper addresses the computation of force fields inside permanent magnets that are used in many magnetic systems. The aim is to stress that magnetic behavior is not sufficient when the B-H constitutive law depends on the mechanical deformation. A full knowledge of B and H may not be enough to unambiguously compute forces. Using two expressions of magnetic energy, both admissible and giving the same B-H relationship, an application of the virtual power principle leads to two distinct force distributions. To prove this, thorough computations are performed: depending on the chosen expression huge differences on deformations are obtained.

Dynamic Modelling and Simulation of Electromechanical Systems Based on Vector Bond Graph

For the dynamic modelling and simulation of electromechanical coupling systems, the corresponding vector bond graph procedure is proposed. Based on the kinematic constraint relations of rigid body, the vector bond graph procedure for modelling spacial multibody systems with revolute joint is described. For the difficulties brought by differential causality in the system automatic modeling and simulation, the effective decoupling method is proposed. As a result, the unified modelling and simulation for electromechanical systems are realized, its validity is illustrated by the robot system driven by electrical motors.

Monitoring Gear Fault by Using Motor Current Signature Analysis and Fast Kurtogram Method

Conventional methods (i.e. time and frequency analysis) can routinely be used to reveal gear fault-indicating information in the current signal. In recent years, Wavelet analysis, which can lead to a clear identification of the nature of faults, are widely used to describe rotating machine condition. The Capability of this method in the detection of any abnormality can be further improved when its low-order frequency moments are considered. This paper presents the use of the Fast Kurtogram in the early detection and condition monitoring of crack fault. For this purpose, a dynamic model of an electromechanical system which is a simple stage gearbox (with and without gear defect) driven by a three phase induction machine is developed. Then motor stator current is analyzed by using a Fast Kurtogram method. This method is suitable for such diagnosis and gives valuable information about the presence and effects of the crack tooth defect

ANN model of RF MEMS Lateral SPDT switches for millimeter wave applications

This paper presents Artificial Neural Network (ANN) implementation for the Radio Frequency (RF) and Mechanical modeling of lateral RF Micro Electro Mechanical System (MEMS) series micro machined Single pole double through (SPDT) switch. We propose an efficient approach based on ANN for analyzing the losses in ON and OFF state of lateral RF MEMS series switch by calculating the S-parameters. The double beam structure has been analyzed in terms of its return, isolation and insertion losses with the variation of its passive circuit component values. The effect of design parameters has been analyzed and the lateral switch was realized with low insertion loss, high return and isolation losses. ANN model were trained with five different training algorithms namely Levenberg-Marquart (LM), Bayesian Regularization (BR), Quasi - Newton (QN), Scaled Conjugate Gradient (SCG) and Conjugate Gradient of Fletcher - Powell (CGF) to obtain better performance and fast convergence. The results from the neural model trained by Levenberg-Marquardt back propagation algorithm are highly agreed with the theoretical results available in the literature. The neural networks shows the better results with the highest correlation coefficient which measures the strength and direction of linear relation between two variables (actual and predicted values) (0.9998) along with lowest root mean square error (MSE) of (0.0039).