基于模糊神经网络的金属化薄膜电容器健康监测

M. Makdessi, A. Soualhi, A. Sari, P. Venet, H. Razik, G. Clerc
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引用次数: 1

摘要

近年来,电力电子设备的健康监测成为保障整个电力电子系统可用性的重要环节,受到了人们的广泛关注。直流电容,无论其类型或技术如何,都是需要监测的主要设备之一,因为它们负责超过30%的电力电子设备故障。本文提出了一种基于模糊神经网络的无创电容电参数演化检测方法。后者是基于组件阻抗的实时处理和加速老化试验提供的老化退化数据。对一组10个聚合物薄膜电容器进行了测试,以验证所提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Health monitoring of metallized film capacitors using Neo Fuzzy Neural approach
Recently, special attention has been devoted to the health monitoring aspect of power electronics devices since it became an essential step to ensure and guarantee the availability of the overall power electronics systems. Dc-link capacitors, despite their type or technology are one of the main devices to monitor since they are responsible of more than 30% of the power electronics equipment breakdowns. In this paper, a noninvasive method is proposed in order to detect the capacitors electrical parameter evolution using the Neo Fuzzy Neural approach. This latter is based on the real-time processing of the component's impedance and the ageing degradation data provided from accelerated ageing tests. A set of 10 polymer film capacitors was tested to validate the proposed approach.
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