智能故障诊断技术在高压直流系统中的应用

Zhiqing Yao, Ximei Liu
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引用次数: 2

摘要

由于非线性系统故障诊断的普遍性和复杂性,对其进行研究具有重要的理论和实用价值。迄今为止,针对非线性时滞系统的故障诊断方法很少。针对一类非线性时滞系统,提出了一种基于p型迭代学习的故障诊断与估计方法。与其他方法不同的是,FDEM采用p型迭代学习策略,引入虚拟故障参数逼近实际故障。此外,该方法不仅可以快速跟踪系统故障,而且可以精确估计故障信号。给出了两个典型的非线性时滞系统的仿真结果。在此基础上,对高压直流系统进行了详细的分析,并将FDEM应用于高压直流系统的故障诊断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of intelligent fault diagnosis technology in HVDC system
It has very important theoretical and practical values to research fault diagnosis of nonlinear system because of its universality and complexity. Up to now, there have been few fault diagnosis methods for nonlinear time-delay system. This paper proposes a fault diagnosis and estimation method(FDEM) for a class of nonlinear time-delay system based on P-type iterative learning. Different from the other methods, FDEM introduces a parameter called dummy fault to approach actual fault using P-type iterative learning policy. Besides, FDEM not only can track system fault quickly, but it also can estimate fault signals precisely. Two typical nonlinear time-delay system simulation results are given. Furthermore, HVDC(High Voltage Direct Circuit)system is analyzed detailedly and FDEM is used for fault diagnosis of HVDC system.
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