Analysis of Residual Wavelet Scalogram for Machinery Fault Diagnosis

被引:1
|
作者
Hee, Lim Meng [1 ]
Leong, M. S.
Hui, K. H. [1 ]
机构
[1] Univ Teknol Malaysia, Razak Sch Engn & Adv Technol, Skudai, Johor, Malaysia
关键词
Residual; Wavelet; Coefficient; Machinery; Fault Analysis; ROTOR SYSTEM; TRANSFORM; CRACK;
D O I
10.4028/www.scientific.net/AMR.845.113
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Wavelet analysis is a very useful tool for machinery faults diagnosis. However, actual application of wavelet analysis for machinery fault diagnosis in the field is still relatively rare. This is partly due to the fact that visual interpretation of wavelet results is often difficult and very challenging. This paper investigates an effective method to present wavelet analysis results in order to simplify the interpretation of wavelet analysis result for machinery faults diagnosis. Analysis of residual wavelet scalogram was proposed in this study as a mean to display and extract key faults signatures from raw sensor signals. Simulated signals were generated to test the feasibility of the proposed method. Test results showed that the proposed wavelet method provides a simple and more effective way to diagnose machinery faults.
引用
收藏
页码:113 / 117
页数:5
相关论文
共 50 条
  • [31] Fault Diagnosis of Rotating Machinery Base on Wavelet Packet Energy Moment and HMM
    Zhang, C. L.
    Yue, X.
    Li, S.
    Li, J.
    MANUFACTURING AUTOMATION TECHNOLOGY DEVELOPMENT, 2011, 455 : 558 - +
  • [32] Fault diagnosis of rotating machinery based on harmonic wavelet fuzzy neural networks
    Peng, Bin
    Liu, Zhen-Quan
    Dongli Gongcheng/Power Engineering, 2005, 25 (05): : 702 - 706
  • [33] Research on Aeroengine Rub-impact Fault Analysis Based on Wavelet Scalogram Statistical Feature
    Wu Yahui
    Zhang Dazhi
    Li Xinliang
    Xue Jingfeng
    MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION, PTS 1 AND 2, 2011, 48-49 : 942 - 945
  • [34] Using wavelet scalogram for vibration signals analysis
    Peng, Zhike
    He, Yongyong
    Chu, Fulei
    Jixie Gongcheng Xuebao/Chinese Journal of Mechanical Engineering, 2002, 38 (03): : 122 - 126
  • [35] Wavelet transform based on inner product in fault diagnosis of rotating machinery: A review
    Chen, Jinglong
    Li, Zipeng
    Pan, Jun
    Chen, Gaige
    Zi, Yanyang
    Yuan, Jing
    Chen, Binqiang
    He, Zhengjia
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2016, 70-71 : 1 - 35
  • [36] Rotating machinery fault diagnosis based on improved wavelet fuzzy neural network
    Peng, B
    Liu, ZQ
    PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON QUALITY & RELIABILITY, 2005, : 781 - 786
  • [38] A New Method for Fault Diagnosis of Rotating Machinery Based on Harmonic Wavelet Filtering
    Zhang, Wenbin
    Cai, Qun
    Shen, Lu
    Wang, Hongjun
    Li, Junsheng
    PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9, 2009, : 3935 - +
  • [39] Fault Diagnosis of Rotating Machinery Based on Wavelet Domain Denoising and Metric Distance
    Su, Naiquan
    Li, Xiao
    Zhang, Qinghua
    IEEE ACCESS, 2019, 7 : 73262 - 73270
  • [40] ROTATING MACHINERY FAULT DIAGNOSIS METHOD BASED ON IMPROVED RESIDUAL NEURAL NETWORK
    Xu S.
    Deng A.
    Yang H.
    Fan Y.
    Deng M.
    Liu D.
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2023, 44 (07): : 409 - 418