Enhanced periodic mode decomposition and its application to composite fault diagnosis of rolling bearings

被引：32
|
作者：
Cheng, Jian [1 ]
Yang, Yu [1 ]
Shao, Haidong [1 ]
Pan, Haiyang [2 ]
Zheng, Jinde [2 ]
Cheng, Junsheng [1 ]
机构：
[1] Hunan Univ, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Peoples R China
[2] Anhui Univ Technol, Sch Mech Engn, Maanshan 243032, Peoples R China
来源：
ISA TRANSACTIONS | 2022年 / 125卷
关键词：
Enhancedperiodicmodedecomposition; Ramanujansum; SOSO-MAIHND; Rollingbearing; Compositefaultdiagnosis;
D O I：
10.1016/j.isatra.2021.07.014
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The impulse components of different periods in the composite fault signal of rolling bearing are extracted difficultly due to the background noise and the coupling of composite faults, which greatly affects the accuracy of composite fault diagnosis. To accurately extract the periodic impulse components from the composite fault signals, we introduce the theory of Ramanujan sum to generate the precise periodic components (PPCs). In order to comprehensively extract major periods in composite fault signals, the SOSO-maximum autocorrelation impulse harmonic to noise deconvolution (SOSO-MAIHND) method is proposed to reduce noise and enhance the relatively weak periodic impulses. Based on this, an enhanced periodic mode decomposition (EPMD) method is proposed. The experimental results indicate that the EPMD is an effective method for composite fault diagnosis of rolling bearings. (C) 2021 ISA. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：474 / 491
页数：18
相关论文
共 50 条
  • [31] Fault Diagnosis for Rolling Bearings Using Optimized Variational Mode Decomposition and Resonance Demodulation
    Zhang, Chunguang
    Wang, Yao
    Deng, Wu
    ENTROPY, 2020, 22 (07)
  • [32] Research on variational mode decomposition in rolling bearings fault diagnosis of the multistage centrifugal pump
    Zhang, Ming
    Jiang, Zhinong
    Feng, Kun
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2017, 93 : 460 - 493
  • [33] Application of improved enhanced kurtogram and enhanced envelope spectrum in fault diagnosis of rolling bearings
    Wang, X.-L., 1600, Chinese Vibration Engineering Society (33):
  • [34] An Improved Method of EWT and Its Application in Rolling Bearings Fault Diagnosis
    Qiao, Zhicheng
    Liu, Yongqiang
    Liao, Yingying
    SHOCK AND VIBRATION, 2020, 2020 (2020)
  • [35] Spectral band refined composite multiscale fuzzy entropy and its application in fault diagnosis of rolling bearings
    Tong S.-G.
    Zhang Y.-D.
    Xu J.
    Cong F.-Y.
    Cong, Fei-Yun (cloudswk@zju.edu.cn), 2018, Zhejiang University (52): : 1509 - 1516
  • [36] Compound fault diagnosis method for rolling bearings based on enhanced MED and adaptive periodized symplectic geometry mode decomposition
    Li, Shengqiang
    Yan, Changfeng
    Hou, Yunfeng
    Liu, Bin
    Tian, Yu
    Wu, Lixiao
    STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2025,
  • [37] Improved Empirical Mode Decomposition and Its Application to Fault Diagnosis of Train's Rolling Bearing
    He, Ping
    Sun, Nanxiang
    Sun, Huiqi
    Li, Pan
    Shang, Wei
    2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL VII, 2010, : 181 - 184
  • [38] Clustering Group-Sparse Mode Decomposition and Its Application in Rolling Bearing Fault Diagnosis
    Pang, Bin
    Wang, Bocheng
    Hu, Yuzhi
    Cheng, Tianshi
    Xu, Zhenli
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 71
  • [39] A Fast and Adaptive Empirical Mode Decomposition Method and Its Application in Rolling Bearing Fault Diagnosis
    Li, Yun
    Zhou, Jiwen
    Li, Hongguang
    Meng, Guang
    Bian, Jie
    IEEE SENSORS JOURNAL, 2023, 23 (01) : 567 - 576
  • [40] The Partial Reconstruction Symplectic Geometry Mode Decomposition and Its Application in Rolling Bearing Fault Diagnosis
    Liu, Yanfei
    Cheng, Junsheng
    Yang, Yu
    Bin, Guangfu
    Shen, Yiping
    Peng, Yanfeng
    SENSORS, 2023, 23 (17)
12345