集成全息希尔伯特谱分析及其在滚动轴承故障诊断中的应用

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振动与冲击 ›› 2024, Vol. 43 ›› Issue (13) : 98-105.

论文

彭国良1，郑近德1，潘海洋1，童靳于1，刘庆运1

作者信息 +

Ensemble holo-Hilbert spectral analysis and its application in fault diagnosis of rolling bearing

PENG Guoliang1, ZHENG Jinde1, PAN Haiyang1, TONG Jinyu1, LIU Qingyun1

Author information +

文章历史 +

摘要

全息希尔伯特谱分析(Holo-Hilbert spectral analysis，HHSA)是一种新的信号解调分析处理技术，其采用双层经验模态分解(EMD)，能够有效揭示非线性或非平稳振动信号中的跨尺度耦合关系。但是，EMD在信号分解过程中存在严重的模态混叠问题，导致瞬时频率估计不准确，影响了HHSA的分析精度。基于此，论文提出了集成全息希尔伯特谱分析(Ensemble Holo-Hilbert spectral analysis，EHHSA)方法。同时为了更精确解调故障特征信息，通过对载波变量进行积分，定义了一种可以揭示调制特征的调幅边际谱分析方法。最后，通过对滚动轴承仿真和实测数据进行分析，结果表明：与传统谱分析方法相比，所提EHHSA方法及调幅边际谱的特征提取性能和噪声鲁棒性更强。

Abstract

Holo-Hilbert spectral analysis (HHSA) is a new signal processing technique that utilizes double-layer empirical mode decomposition (EMD) to reflect the cross scale coupling relationships in nonlinear and non-stationary vibration signals. However, there is a serious mode mixing problem in the signal decomposition process of EMD, which leads to inaccurate Instantaneous phase and frequency estimation and affects the analysis accuracy of HHSA. Based on this, an ensemble Holo-Hilbert spectral analysis (EHHSA) method is proposed. In the analysis process based on EHHSA, an amplitude modulation marginal spectrum analysis method that can reveal modulation characteristics was defined by integrating carrier variables. Finally, the analysis of simulation and measured data on rolling bearings shows that the proposed EHHSA method and amplitude modulation marginal spectrum have stronger feature extraction performance and noise robustness compared to traditional spectral analysis methods.

导出引用

彭国良1，郑近德1，潘海洋1，童靳于1，刘庆运1. 集成全息希尔伯特谱分析及其在滚动轴承故障诊断中的应用[J]. 振动与冲击, 2024, 43(13): 98-105

PENG Guoliang1, ZHENG Jinde1, PAN Haiyang1, TONG Jinyu1, LIU Qingyun1. Ensemble holo-Hilbert spectral analysis and its application in fault diagnosis of rolling bearing[J]. Journal of Vibration and Shock, 2024, 43(13): 98-105

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