电子测量与仪器学报

刘奇,王衍学.基于 ACMD 和脊检测的滚动轴承非平稳故障诊断[J].电子测量与仪器学报,2021,35(8):70-78

基于 ACMD 和脊检测的滚动轴承非平稳故障诊断

Fault diagnosis of non-stationary rolling bearing based onadaptive chirp mode decomposition and ridge detection

DOI：

英文关键词:adaptive chirp mode decomposition non-stationary rolling bearing fault diagnosis time-frequency analysis

基金项目:国家自然科学基金(51875032,61463010,51475098)、北京建筑大学2021年度研究生创新项目资助

作者	单位
刘奇	1. 北京建筑大学机电与车辆工程学院，2. 北京建筑大学城市轨道交通车辆服役性能保障重点实验室
王衍学	1. 北京建筑大学机电与车辆工程学院，2. 北京建筑大学城市轨道交通车辆服役性能保障重点实验室

Author	Institution
Liu Qi	1. School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture,2. Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing University of Civil Engineering and Architecture
Wang Yanxue	1. School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture,2. Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing University of Civil Engineering and Architecture

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中文摘要:

针对非平稳状况滚动轴承振动信号易受速度波动、幅值或频率调制、噪声和其他无关分量的干扰,导致生成的时频面复杂,难以识别滚动轴承故障特征频率等问题,提出一种新的基于自适应调频模式分解和脊检测相结合的方法。所提出的方法构建了高分辨率的时频表示,提升了诊断的准确度,而且具有非常强的自适应性。通过对不同健康状况滚动轴承振动信号分析发现,所提方法非常适合于变工况下的滚动轴承故障诊断,且诊断效果优于最新发展的时频分析方法。

英文摘要:

In view of the fact that the vibration signal of rolling bearing under non-stationary conditions is vulnerable to the interference of velocity fluctuation, amplitude or frequency modulation, noise and other irrelevant components, which leads to the complexity of the generated time-frequency plane, and makes it difficult to identify the fault characteristic frequency of rolling bearing. A novel method based on adaptive chirp mode decomposition and ridge detection is proposed. The proposed method constructs a high-resolution timefrequency representation, improves the accuracy of diagnosis, and has very strong adaptability. Through the analysis of the vibration signals of rolling bearing with different health conditions, it is found that the proposed method is very suitable for fault diagnosis of rolling bearing under variable speed conditions, and the diagnosis effect is better than the newly developed time-frequency analysis method.

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