一种改进基尼指数加权的轴承健康指标构建方法

doi:10.3969/j.issn.1004-132X.2023.15.006

中国机械工程 ›› 2023, Vol. 34 ›› Issue (15): 1813-1819，1855.DOI: 10.3969/j.issn.1004-132X.2023.15.006

一种改进基尼指数加权的轴承健康指标构建方法

钱门贵1;陈涛1;于耀翔1;郭亮1;高宏力1;李威霖2,3

1.西南交通大学机械工程学院，成都，610031
2.浙江方圆检测集团股份有限公司，杭州，310018
3.浙江省市场监管新能源汽车驱动系统重点实验室，杭州，310014

出版日期:2023-08-10 发布日期:2023-08-14
通讯作者: 郭亮（通信作者），男，1988年生，副教授。研究方向为轨道交通设备智能维护与健康管理、健康指标构建、智能故障诊断与预测、边云协作系统、智能维护机器人等。发表论文50余篇，获专利20余项。E-mail:guolaing@.swjtu.edu.com。
作者简介:钱门贵，男，1998年生，硕士研究生。研究方向为机械信号分析与处理、机械健康监测与智能维护。
基金资助:
国家自然科学基金(51905452,51775452)；中央引导地方科技发展资金(2020ZYD012)；浙江省市场监督管理局雏鹰计划培育项目(CY2022111)；四川省科技项目(2021YFG0068)

A Method for Constructing Bearing HIs with IGI Weighting

QIAN Mengui1;CHEN Tao1;YU Yaoxiang1;GUO Liang1;GAO Hongli1;LI Weilin2,3

1.School of Mechanical Engineering,Southwest Jiaotong University,Chengdu,610031
2.Zhejiang Fangyuan Test Group Co.,Ltd.,Hangzhou,310018
3.Key Laboratory of New Energy Automotive Drive Systems for Zhejiang Market Regulation,
Hangzhou,310014

Online:2023-08-10 Published:2023-08-14

摘要/Abstract

摘要： 在轴承的状态监测中，构建一个可以准确描述轴承退化趋势且能及时识别早期退化点(EDP) 的健康指标(HI) 至关重要。目前大多学者提出的健康指标能较好地描述轴承的退化趋势，但不能准确识别早期退化点。提出了一种改进基尼指数(IGI) 加权的轴承健康指标构建方法。利用集成经验模态分解(EEMD) 对原始信号进行分解，根据各分量的故障特征能量比(FCER)，对其进行加权重构得到重构信号；计算重构信号的IGI；将IGI作为重构信号的FCER进行加权计算，得到最终的指标IGI-FCER-HI。通过两个实验验证了所提方法的有效性，并与其他健康指标进行了对比。结果表明，所提方法构建的指标不仅具有良好的单调性和趋势性，而且能准确监测轴承的早期退化点。

关键词: 滚动轴承, 早期退化点, 健康指标, 集成经验模态分解, 加权重构的集成经验模态分解, 故障特征能量比, 改进的基尼指数

Abstract: In the bearings condition monitoring, it was important to construct a HI that might accurately describe bearings degradation trends and identify EDP. At present, most of HIs proposed might describe the degradation trends of bearings well, but could not accurately identify the EDP. A method for constructing bearing HIs was proposed with IGI weighting. The original signals were decomposed by using EEMD, and the reconstructed signals were weighted according to the FCER of each components. The IGI of the reconstructed signals was calculated.The IGI was weighted as the FCER of the reconstructed signals to obtain the final IGI-FCER-HI. The effectiveness of the method was verified by two experiments. The results show that the IGI-FCER-HI has well monotonicity and trend, may identify EDPs of bearings accurately.

Key words: rolling bearing, early degradation point(EDP), health indicator(HI), ensemble empirical mode decomposition(EEMD), weighted reconstructed EEMD, failure characteristic energy ratio(FCER), improved Gini index(IGI)

中图分类号:

TH133

钱门贵, 陈涛, 于耀翔, 郭亮, 高宏力, 李威霖, . 一种改进基尼指数加权的轴承健康指标构建方法[J]. 中国机械工程, 2023, 34(15): 1813-1819，1855.

QIAN Mengui, CHEN Tao, YU Yaoxiang, GUO Liang, GAO Hongli, LI Weilin, . A Method for Constructing Bearing HIs with IGI Weighting[J]. China Mechanical Engineering, 2023, 34(15): 1813-1819，1855.

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一种改进基尼指数加权的轴承健康指标构建方法

A Method for Constructing Bearing HIs with IGI Weighting

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