自适应谱峭度图及其在滚动轴承故障诊断中的应用
何倩，易彩，吴文逸，林建辉
（西南交通大学 牵引动力国家重点实验室，四川 成都 610031）
摘要：提出了一种新的自适应谱峭度图方法。首先采用CEEMDAN方法分解信号的傅里叶频谱，然后对得到的低频IMF分量与残差项进行分层累加计算，对每一层的频谱趋势寻找极小值点，使其作为频谱划分边界，将划分后的各频段通过正交滤波器并利用峭度指标对划分后信号中的故障信息进行评估，构造出一种新的自适应谱峭度图。该方法能够克服快速谱峭度图因遵循固定划分规则易使检测出的频带不能包含完整的故障信息或是提取到无效分量的情况，并且分别利用轴承外圈故障的仿真信号和试验信号，验证了该方法的有效性。
关键词：故障诊断；自适应谱峭度图；频谱趋势；快速谱峭度图
中图分类号：TH133.33；TN911.7 文献标志码：A doi：10.3969/j.issn.1006-0316.2022.11.002
文章编号：1006-0316 (2022) 11-0009-10
Adaptive Spectral Kurtosis Map and Its Application in Fault Diagnosis of Rolling Bearings
HE Qian，YI Cai，WU Wenyi，LIN Jianhui
( State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, China )
Abstract：A new adaptive spectral kurtosis map method is proposed in this paper. First, the CEEMDAN methods are applied to decompose signal Fourier spectrum. Then the low-frequency IMF component and residuals are obtained and performed layered incremental calculation. The minimum points of frequency spectrum trend of each layer are found and made as spectrum division boundaries. The divided frequency bands pass through orthogonal spectrum filter and the fault information in the signal is evaluated by the kurtosis index to construct a new adaptive spectrum kurtosis map. This method can overcome the problem that the detected frequency band may not contain complete fault information or may extract invalid components by following fixed division rules. And the effectiveness of the method was verified by using the simulation signal and the test signal of bearing outer ring failure respectively.
Key words：fault diagnosis；adaptive spectral kurtosis map；spectral trend；fast spectral kurtosis map
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收稿日期：2022-02-25
基金项目：国家自然科学基金（51905453）；中国博士后面上基金（2019M663899XB）；中央高校基本科研业务费项目（2682020CX50）；牵引动力国家重点实验室自主课题（2020TPL-T14）
作者简介：何倩（1996－），女，四川南充人，硕士研究生，主要研究方向为机械设备故障诊断与信号分析，E-mail：h243052028@163.com。
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