Limitations of vibration demodulation analysis application in machine fault diagnosis

被引:0
|
作者
Ding, K [1 ]
Jiang, LQ [1 ]
机构
[1] Shantou Univ, Dept Mechatron Engn, Guangdong 515063, Peoples R China
关键词
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Demodulation analysis is widely used to diagnose the faults of machines fixed gear and bearing. From theoretical analysis, we know the existing demodulation methods have three limitations as following: when we demodulate two time-domain adding signals without modulating information (fault information), the subtraction of the two signals' frequencies will display as the result of demodulation; in generalized detection-filtering demodulation analysis, the effect of frequency aliasing may arise as a result of getting absolute value or detection; in several new Zoom demodulation methods, because digital low-pass filtering can not be carried out in the process of Zoom sub-sampling, it is possible to occur the phenomenon of frequency aliasing at low frequency range, which is the overlap of the higher harmonics of modulation frequency. This paper presents an optimized Hilbert Transform demodulation method based upon complex analytic band-pass filter, which can overcome the three limitations if the analytical frequency of modulation and filter's bandwidth satisfy a strict mathematics relation between themselves. Meanwhile, we can integrate band-pass filtering, Hilbert transform and sub-sampling as a whole to obtain a fast operation. It is an optimized demodulation method.
引用
收藏
页码:128 / 137
页数:10
相关论文
共 50 条
  • [41] Machine fault detection and diagnostics using vibration analysis
    Randall, R.B.
    Acoustics Australia, 1994, 22 (03)
  • [42] Application of black box to fault diagnosis of rotating machine
    Zhang, J.X.
    Xu, M.Q.
    Huang, W.H.
    Zhang, J.Y.
    Zhang, G.B.
    Journal of Harbin Institute of Technology (New Series), 2001, 8 (01) : 83 - 86
  • [43] Parameterized Synchrosqueezing Transform With Application to Machine Fault Diagnosis
    Tu, Xiaotong
    Bao, Wenjie
    Hu, Yue
    Abbas, Saqlain
    Li, Fucai
    IEEE SENSORS JOURNAL, 2019, 19 (18) : 8107 - 8115
  • [44] Application of Hidden Markov Models in Machine Fault Diagnosis
    Kang, Jian-She
    Zhang, Xing-Hui
    INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL, 2012, 15 (12B): : 5829 - 5838
  • [45] Local discriminant bases in machine fault diagnosis using vibration signals
    Tafreshi, R
    Sassani, F
    Ahmadi, H
    Dumont, G
    INTEGRATED COMPUTER-AIDED ENGINEERING, 2005, 12 (02) : 147 - 158
  • [46] Vibration Fault Diagnosis of Rotating Machine based on the Principle of Entropy Increase
    Yu, Chen
    Li, Jianlan
    Huang, Shuhong
    SMART TECHNOLOGIES FOR MATERIALS, 2012, 530 : 109 - 114
  • [47] Model construction and application of machinery fault diagnosis of ships based on technology of resonant demodulation
    Wang, Shilai, 1600, Academy of Sciences of the Czech Republic, Dolejskova 5, Praha 8, 182 00, Czech Republic (62):
  • [48] Application of fault diagnosis method based on EMD and energy operator demodulation to hoist gearbox
    Leng, J.-F. (lengjf@hpu.edu.cn), 1600, China Coal Society (38):
  • [49] Rotor vibration fault fusion diagnosis based on support vector machine
    Ai, Yan-Ting
    Fei, Cheng-Wei
    Shenyang Gongye Daxue Xuebao/Journal of Shenyang University of Technology, 2010, 32 (05): : 526 - 530
  • [50] Diagnosis of rotating machine defects by vibration analysis
    Bouaouiche, Karim
    Menasria, Yamina
    Khalfa, Dalila
    ACTA IMEKO, 2023, 12 (01):