地铁电源模块故障分析及预测方法

doi:10.12068/j.issn.1005-3026.2022.01.002

东北大学学报（自然科学版） ›› 2022, Vol. 43 ›› Issue (1): 8-16.DOI: 10.12068/j.issn.1005-3026.2022.01.002

地铁电源模块故障分析及预测方法

宫琦¹，陈秉智²，李永华²，夏清¹

)(1. 大连交通大学机械工程学院，辽宁大连116028; 2. 大连交通大学机车车辆工程学院，辽宁大连116028)

修回日期:2021-04-13 接受日期:2021-04-13 发布日期:2022-01-25
通讯作者: 宫琦
作者简介:宫琦(1980-)，女，辽宁大连人，大连交通大学博士研究生；陈秉智(1971-)，男，浙江宁波人，大连交通大学教授，博士生导师；李永华(1971-)，女，黑龙江青冈人，大连交通大学教授，博士生导师.
基金资助:
国家自然科学基金资助项目(51875073)；辽宁省高等学校创新团队支持计划项目(LT2016010)；大连市科技创新基金资助项目(2019J11CY017)；辽宁省教育厅科学研究项目(LJKZ0503).

Fault Analysis of Metro Power Supply Module and Prediction Method

GONG Qi¹， CHEN Bing-zhi²， LI Yong-hua²， XIA Qing¹

1. School of Mechanical Engineering， Dalian Jiaotong University， Dalian 116028， China; 2. School of Locomotive and Rolling Stock Engineering， Dalian Jiaotong University， Dalian 116028， China.

Revised:2021-04-13 Accepted:2021-04-13 Published:2022-01-25
Contact: LI Yong-hua
About author:-
Supported by:
-

摘要/Abstract

摘要： 为提高地铁车辆牵引逆变系统的可靠性，对牵引逆变系统电源模块进行故障问题的跟踪研究.首先，在电源模块运用初期，针对其烧毁问题，提出整改方案.然后，提出一个新的故障预测方法.运用傅里叶级数和马尔可夫理论对预测残差分别进行一次和二次修正，建立改进的灰色预测模型，引入新陈代谢法进行最终预测.最后，为验证方法的有效性，以运用8.5年的电源模块故障数据为例，将几种预测方法进行比较，结果表明，所提方法具有更高的预测精度和一定的工程应用价值.

关键词: 电源模块;故障分析;预测模型;改进的灰色模型;新陈代谢

Abstract: In order to improve the reliability of the metro traction inverter system， the tracking research on the failure of the power supply module in the traction inverter system is carried out. First， during the initial stage of the power module application， the rectification is presented for the burning problem. Then， a new failure prediction method is proposed. Fourier series and Markov theory are used to modify the prediction residuals once and twice， respectively. The improved grey model is established. The metabolism is introduced to make the final prediction. Finally， in order to verify the effectiveness of the method， several prediction methods are compared by the power module fault data of 8.5 years. The results show that the proposed method has a higher prediction accuracy and certain engineering application value.

Key words: power supply module; fault analysis; prediction model; improved grey model; metabolism

中图分类号:

U223.6

宫琦，陈秉智，李永华，夏清. 地铁电源模块故障分析及预测方法[J]. 东北大学学报（自然科学版）, 2022, 43(1): 8-16.

GONG Qi， CHEN Bing-zhi， LI Yong-hua， XIA Qing. Fault Analysis of Metro Power Supply Module and Prediction Method[J]. Journal of Northeastern University(Natural Science), 2022, 43(1): 8-16.

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地铁电源模块故障分析及预测方法

Fault Analysis of Metro Power Supply Module and Prediction Method

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