Machine tool fault detection based on order cepstrum

被引:0
|
作者
Li, H. [1 ]
Zheng, H. Q. [1 ]
Tang, L. W. [1 ]
机构
[1] Shijiazhuang Mech Engn Coll, Dept 1, Shijiazhuang 050003, Hebei, Peoples R China
基金
中国国家自然科学基金;
关键词
machine tool; gear; order cepstrum; faults diagnosis; signal processing;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Varying speed machinery condition detection and fault diagnosis are more difficult due to non-stationary vibration. In order to process the non-stationary vibration signals such as speed-up or speed-down vibration signals effectively, the order cepstrum analysis technique is presented. This new method combines computed order tracking technique with cepstrum analysis. Firstly, the vibration signal is sampled at constant time increments and then uses numerical techniques to resample the data at constant angle increments. Therefore, the vibration signals are transformed from the time domain transient signal to angle domain stationary one. In the end, the resampled signals are processed by cepstrum analysis method. The experimental results show that order cepstrum analysis can effectively diagnosis the faults of the gear crack.
引用
收藏
页码:411 / +
页数:2
相关论文
共 50 条
  • [31] Gear fault detection based on relevance vector machine
    Automotive Engineering College, South China Univ. of Technol., Guangzhou 510640, China
    J Vib Shock, 2008, 6 (51-54): : 51 - 54
  • [32] COMPUTER HARDWARE FAULT DETECTION BASED ON MACHINE LEARNING
    Xu, Chunxue
    SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2023, 24 (04): : 699 - 712
  • [33] Machine Learning Fault Detection Algorithm Based On Resampling
    Dong, Mianmian
    He, Mimi
    Zhao, Yihan
    Wang, Peng
    Di, Ruohai
    Wu, Jiao
    2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 3158 - 3163
  • [34] Relevance Vector Machine Based Gear Fault Detection
    He, Chuangxin
    Li, Yanming
    Huang, Yixiang
    Liu, Chengliang
    Fei, Shengwei
    PROCEEDINGS OF THE 2009 CHINESE CONFERENCE ON PATTERN RECOGNITION AND THE FIRST CJK JOINT WORKSHOP ON PATTERN RECOGNITION, VOLS 1 AND 2, 2009, : 731 - 735
  • [35] A New Formant Detection Algorithm Based on Cepstrum
    He Jinbao
    Fan Hongchao
    Yi Xinhua
    Hu Jiafen
    EMERGING SYSTEMS FOR MATERIALS, MECHANICS AND MANUFACTURING, 2012, 109 : 681 - +
  • [36] Endpoint detection of noisy speech based on cepstrum
    Hu, Guangrui
    Wei, Xiaodong
    Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2000, 28 (10): : 95 - 97
  • [37] Cepstrum based detection and classification of OFDM waveforms
    Jantti, Joona
    Chaudhari, Sachin
    Koivunen, Visa
    2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2014,
  • [38] Research on Bearing Fault Diagnosis Based on Slice Spectrum and Cepstrum
    Liu, Long-bo
    3RD INTERNATIONAL CONFERENCE ON APPLIED MECHANICS AND MECHANICAL AUTOMATION (3RD AMMA 2017), 2017, : 23 - 28
  • [39] Vibration fault identification of a turbojet engine based on cepstrum analysis
    Huang, Jingjing
    Zhang, Xijun
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING, 2022, 236 (10) : 1961 - 1970
  • [40] Knitting needle fault detection system for hosiery machine based on laser detection and machine vision
    School of Mechanical and Electrical Engineering, Xi'an Polytechnic University, China
    不详
    Text. Res. J., 1-2 (143-151):