Compound faults detection of rolling element bearing based on the generalized demodulation algorithm under time-varying rotational speed

被引:71
|
作者
Zhao, Dezun [1 ]
Li, Jianyong [1 ]
Cheng, Weidong [1 ]
Wen, Weigang [1 ]
机构
[1] Beijng Jiaotong Univ, Sch Mech Elect & Control Engn, 3 Shangyuancun Haidian Dist, Beijing 100044, Peoples R China
关键词
Rolling element bearing; Compound faults detection; Generalized demodulation algorithm; Time-varying rotational speed; ORDER TRACKING; FREQUENCY ANALYSIS; DIAGNOSTICS;
D O I
10.1016/j.jsv.2016.05.022
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Multi-fault detection of the rolling element bearing under time-varying rotational speed presents a challenging issue due to its complexity, disproportion and interaction. Computed order analysis (COA) is one of the most effective approaches to remove the influences of speed fluctuation, and detect all the features of multi-fault. However, many interference components in the envelope order spectrum may lead to false diagnosis results, in addition, the deficiencies of computational accuracy and efficiency also cannot be neglected. To address these issues, a novel method for compound faults detection of rolling element bearing based on the generalized demodulation (GD) algorithm is proposed in this paper. The main idea of the proposed method is to exploit the unique property of the generalized demodulation algorithm in transforming an interested instantaneous frequency trajectory of compound faults bearing signal into a line paralleling to the time axis, and then the FFT algorithm can be directly applied to the transformed signal. This novel method does not need angular resampling algorithm which is the key step of the computed order analysis, and is hence free from the deficiencies of computational error and efficiency. On the other hand, it only acts on the instantaneous fault characteristic frequency trends in envelope signal of multi-fault bearing which include rich fault information, and is hence free from irrelevant items interferences. Both simulated and experimental faulty bearing signal analysis validate that the proposed method is effective and reliable on the compound faults detection of rolling element bearing under variable rotational speed conditions. The comprehensive comparison with the computed order analysis further shows that the proposed method produces higher accurate results in less computation time. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:109 / 123
页数:15
相关论文
共 50 条
  • [41] Faults’ Diagnosis of Time-Varying Rotational Speed Machinery Based on Vibration and Acoustic Signals Features Extraction, and Machine Learning Methods
    Toufik Bettahar
    Rahmoune Chemseddine
    Djamel Benazzouz
    Journal of Vibration Engineering & Technologies, 2023, 11 : 2333 - 2347
  • [42] Vibration analysis of a deep groove ball bearing with localized and distributed faults subject to waviness based on an improved model under time-varying speed condition
    Cheng, Xiaohan
    Wang, Aiming
    Yang, Hui
    Zhang, Tao
    Cao, Congjie
    Wu, Guangqiang
    JOURNAL OF VIBRATION AND CONTROL, 2023, 29 (13-14) : 3259 - 3274
  • [43] Vold-Kalman generalized demodulation for multi-faults detection of gear and bearing under variable speeds
    Zhao, Dezun
    Li, Jianyong
    Cheng, Weidong
    Wang, Peng
    Gao, Robert X.
    Yan, Ruqiang
    46TH SME NORTH AMERICAN MANUFACTURING RESEARCH CONFERENCE, NAMRC 46, 2018, 26 : 1213 - 1220
  • [44] Feature Extraction of Faulty Rolling Element Bearing under Variable Rotational Speed and Gear Interferences Conditions
    Zhao, Dezun
    Li, Jianyong
    Cheng, Weidong
    SHOCK AND VIBRATION, 2015, 2015
  • [45] Multiple Time-Frequency Curve Classification for Tacho-Less and Resampling-Less Compound Bearing Fault Detection Under Time-Varying Speed Conditions
    Tang, Gang
    Wang, Yatao
    Huang, Yujing
    Wang, Han
    IEEE SENSORS JOURNAL, 2021, 21 (04) : 5091 - 5101
  • [46] Fault diagnosis of rolling bearings under time-varying speed based on the residual attention mechanism and subdomain adaptation
    Zhu P.
    Dong S.
    Li Y.
    Pei X.
    Pan X.
    Zhendong yu Chongji/Journal of Vibration and Shock, 2022, 41 (22): : 293 - 300
  • [47] Compound fault diagnosis of rolling bearings in variable speed based on adaptive chirp mode decomposition and generalized demodulation
    Zhang, Xiaoli
    Luo, Xin
    Xiao, Yong
    Li, Xianyao
    Liang, Wang
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2025, 36 (03)
  • [48] Application of the Generalized Demodulation Time-Frequency Analysis Method to Vibration Signals under Varying Speed
    Li, Yan
    Du, Li
    2018 IEEE 3RD INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC), 2018, : 828 - 831
  • [49] Simulation-driven unsupervised fault diagnosis of rolling bearing under time-varying speeds
    Xu, Zhenli
    Tang, Guiji
    Pang, Bin
    STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2024,
  • [50] Explainable 1DCNN with demodulated frequency features method for fault diagnosis of rolling bearing under time-varying speed conditions
    Lu, Feiyu
    Tong, Qingbin
    Feng, Ziwei
    Wan, Qingzhu
    An, Guoping
    Li, Yilei
    Wang, Meng
    Cao, Junci
    Guo, Tao
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2022, 33 (09)