邱庆刚

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:男

毕业院校:大连理工大学

学位:博士

所在单位:能源与动力学院

电子邮箱:qqgang@dlut.edu.cn

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基于声信号小波包分析的故障诊断

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发表时间:2022-10-10

发表刊物:自动化学报

期号:4

页面范围:554-559

ISSN号:0254-4156

摘要:In order to avoid the difficulty of installing vibration sensors and extracting characteristic frequency vectors for the traditional vibration-based abrasion fault diagnosis on the main bearing of diesel engine, this paper presents a new approach based on wavelet packet images processing of sound signal of diesel engine. Thus, the standard time-frequency distribution images of all fault conditions including the gap abrasion information of the main bearing can be defined. Correspondingly, a gap abrasion fault diagnosis model of the main bearing with images matching is set up. Through comparing the Euclid distance between standard fault image and the test image, the model can recognize the gap abrasion condition. The results show that this method makes the best use of fault information and is simple and effective.

备注:新增回溯数据