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Fault Diagnosis of Capacitance Aging in DC Link Capacitors of Voltage Source Inverters Using Evidence Reasoning Rule

机译:使用证据推理规则,电压源逆变器直流链路电容器电容老化的故障诊断

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摘要

Capacitance aging of DC link capacitors in voltage source inverters (VSIs) is a common fault which can lead to instability of the DC voltage. In such a failure state, although the VSI can still work, its performance gradually deteriorates, resulting in a shorter service life of the equipment. Here, an online monitoring and fault diagnosis method for capacitance aging based on evidence reasoning (ER) rule is presented. Features from the DC link voltage data with different levels of capacitance aging are extracted, and data features are generated as pieces of diagnostic evidence, which are then combined according to the ER rule. Finally, capacitance aging fault levels were estimated using the combined results. This method has better diagnostic performance compared to a backpropagation (BP) neural network approach and can be used to flexibly define the relative weighting of each evidence parameter depending on the application. This approach can therefore be widely used for fault diagnosis of an array of different devices.
机译:电压源逆变器(VSIS)中DC链路电容器的电容老化是一个常见的故障,可以导致直流电压的不稳定性。在这种失败状态下,虽然VSI仍然可以工作,但其性能逐渐恶化,导致设备的使用寿命较短。这里,提出了基于证据推理(ER)规则的电容老化的在线监测和故障诊断方法。从DC链路电压数据中提取具有不同电容老化级别的DC链路电压数据,并且数据特征被生成为诊断证据,然后根据ER规则组合。最后,使用组合结果估计电容老化故障水平。与BackProjagation(BP)神经网络方法相比,该方法具有更好的诊断性能,并且可用于灵活地定义每个证据参数的相对加权,具体取决于应用。因此,这种方法可以广泛用于不同设备阵列的故障诊断。

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