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Fault Diagnosis for Nonlinear Mechatronic System Using Particle Swarm Optimization

机译:使用粒子群优化的非线性机电系统的故障诊断

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This paper deals with the fault diagnosis of nonlinear mechatronic system using bond graph and particle swarm optimization. The mechatronic system under investigation includes a DC motor with a load part. Nonlinear phenomena such as friction and backlash are considered in the monitored system. The objective of fault diagnosis is to determine the fault source and estimate its magnitude. In order to realize the task in the application, the bond graph modeling tool is adopted to carry out fault detection and isolation. After the potential faults that could lead to the observed fault symptom are obtained, the particle swarm optimization is utilized for fault estimation purpose. Numerical simulations are performed to illustrate the effectiveness of the developed method.
机译:本文涉及使用粘合图和粒子群优化的非线性机电系统的故障诊断。正在研究的机电调整系统包括具有负载部分的直流电动机。在监控系统中考虑了摩擦和间隙等非线性现象。故障诊断的目的是确定故障源并估计其幅​​度。为了实现应用中的任务,采用键盘图建模工具进行故障检测和隔离。在获得可能导致观察到的故障症状的潜在故障之后,粒子群优化用于故障估计目的。执行数值模拟以说明开发方法的有效性。

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