基于实验数据分析的PWM变换器非线性故障早期检测新技术

Y. Kolokolov, A. Monovskaya, P. Ustinov, A. Hamzaoui, N. Essounbouli
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引用次数: 1

摘要

在PWM能量变换器(PEC)动力学中,由于分岔引起的非线性现象导致的故障是最严重的负面后果之一,因为它会导致运行过程稳定性的丧失和动力学的重大变化。从实际应用的角度来看,解决这一问题的较好方法似乎是在PEC运行过程中基于实时数据分析的早期故障检测。然而,所分析的数据包含非线性和噪声成分,这些成分随时间以复杂的方式“混合”。因此,至少有必要综合分岔、谱和统计方法的可能性。本文提出并讨论了这种新技术,它能明显地减少分岔图上的不确定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New technique of experimental data analysis for early detection of PWM converter faults owing to nonlinear phenomena
Faults owing to nonlinear phenomena concerned with bifurcations in PWM energy converter (PEC) dynamics lead to one of the hardest negative consequences since it suppose the loss of operating process stability and crucial changes in the dynamics. From the practical viewpoint the preferable way out of this problem seems to be in early fault detection based on real-time data analysis while PEC operation. However the analyzed data contain nonlinear and noise components which are “mixed” over time by intricate manner. So, it is necessary at least integrate possibilities of the bifurcation, spectrum and statistical methods. In the paper such new technique allowing a visible reduction of uncertainties on bifurcation diagrams is proposed and discussed.
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