Minimum noise amplitude deconvolution and its application in repetitive impact detection

被引：27
作者：
Fang, Bo [1 ,2 ]
Hu, Jianzhong [1 ]
Yang, Cheng [1 ]
Chen, XueMing [3 ]
机构：
[1] Southeast Univ, Sch Mech Engn, 2 DongNanDaXue Rd, Nanjing 211189, Peoples R China
[2] Power China Zhongnan Engn Corp Ltd, Changsha, Peoples R China
[3] State Grid Jiangsu Elect Power Co Ltd, Skill Training Ctr, Suzhou, Peoples R China
来源：
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL | 2023年 / 22卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Blind deconvolution; repetitive impacts; fault diagnosis; rotating machinery; rolling element bearing; resonance demodulation; ROLLING ELEMENT BEARINGS; ENTROPY DECONVOLUTION; BLIND DECONVOLUTION; CYCLOSTATIONARITY; DIAGNOSTICS; INDICATORS; KURTOSIS; MODEL;
D O I：
10.1177/14759217221114527
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Blind deconvolution (BD) is an effective technology for rotating machinery fault detection because it significantly weakens noise and reduces the interference of the system transmission path. This paper analyses the possible shortcomings of several popular BDs in detecting repetitive impacts hidden in rotating machinery signals. Then a new index named periodic noise amplitude ratio (PNAR) is defined to measure the noise level of fault signals. Minimum noise amplitude deconvolution (MNAD) is a new BD algorithm based on PNAR minimization. Unlike the existing BDs, MNAD does not focus on the impacts with certain randomness in their moments of occurrence but enhances the repetitive impact characteristics by weakening the defined periodic noise. MNAD is particularly suitable for detecting repetitive impacts hidden in cyclostationary signals. Simulation analysis and experimental results show that MNAD adaptively determines one or more resonance bands generated by repetitive impacts and has a good suppression effect on the noise in the resonance bands. The implementation of MNAD is available in MATLAB community.
引用
收藏
页码：1807 / 1827
页数：21
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