Fault Diagnosis of Gear Crack Based on Transient Acoustic Signal and Order Cepstrum

被引：0
|
作者：
Tian Hao [1 ]
Tang Liwei [1 ]
Zheng Haiqi [1 ]
Zhang Lei
Yang Tongqiang [1 ]
机构：
[1] Ordnance Engn Coll, Weapon Test Ctr, Shijiazhuang 050003, Peoples R China
来源：
PROCEEDINGS OF THE SECOND INTERNATIONAL SYMPOSIUM ON TEST AUTOMATION & INSTRUMENTATION, VOLS 1-2 | 2008年
关键词：
Transient acoustic signal; order analysis; cepstrum; gear crack; fault diagnosis;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
According to the restriction of self-propelled gun full-scale test, and because the traditional vibration test can't be used for non-contact, non-disassembly and nondestructive test, a method that utilizes the transient acoustic signal for gearbox fault diagnosis was introduced. Combined with the order cepstrum analysis, the disadvantage of traditional FFT in processing non-stationary signal is conquered. Compared to the vibration signals, the gearbox gear crack fault experiment and data analysis showed its feasibility and superiority.
引用
收藏
页码：163 / 167
页数：5
相关论文
共 50 条
  • [1] Research on Order Cepstrum Method for Gear Cracking Fault Diagnosis
    Liu, Xin-Hai
    Zhang, Yan
    Wang, Bao-Bao
    Li, Xue-Dong
    Zhang, Wei
    [J]. 2015 International Conference on Mechanical Engineering and Automation (ICMEA 2015), 2015, : 93 - 97
  • [2] The application of cepstrum in gear fault diagnosis
    Cheng, H
    Cheng, MQ
    Yun, XY
    [J]. ISTM/2005: 6TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-9, CONFERENCE PROCEEDINGS, 2005, : 4830 - 4833
  • [3] Gear crack fault diagnosis based on embedded sensors
    嵌入式传感器的齿轮裂纹故障诊断
    [J]. Ning, Shaohui, 2018, Chinese Vibration Engineering Society (37):
  • [4] Application of order cepstrum and neural network to gear fault detection
    Ai, Shufeng
    Li, Hui
    [J]. 2006 IMACS: MULTICONFERENCE ON COMPUTATIONAL ENGINEERING IN SYSTEMS APPLICATIONS, VOLS 1 AND 2, 2006, : 1822 - +
  • [5] Research on gear crack fault diagnosis model based on permanent magnet motor current signal
    Sheng, Lianchao
    Sun, Qi
    Li, Wei
    Ye, Guo
    [J]. ISA TRANSACTIONS, 2023, 135 : 188 - 198
  • [6] Crack fault diagnosis of gear based on EMD-Wigner higher order moment spectrum
    Cai, Jianhua
    Gong, Yurong
    Wang, Xianchun
    [J]. Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis, 2013, 33 (06): : 1044 - 1048
  • [7] AN EARLY GEAR FAULT DIAGNOSIS METHOD BASED ON RLMD, HILBERT TRANSFORM AND CEPSTRUM ANALYSIS
    Afia, Adel
    Rahmoune, Chemseddine
    Benazzouz, Djamel
    [J]. MECHATRONIC SYSTEMS AND CONTROL, 2021, 49 (02): : 115 - 123
  • [8] Gear Fault Diagnosis through Vibration and Acoustic Signal Combination Based on Convolutional Neural Network
    Yu, Liya
    Yao, Xuemei
    Yang, Jing
    Li, Chuanjiang
    [J]. INFORMATION, 2020, 11 (05)
  • [9] GEAR PITTING FAULT DIAGNOSIS USING RAW ACOUSTIC EMISSION SIGNAL BASED ON DEEP LEARNING
    Li, Xueyi
    Li, Jialin
    He, David
    Qu, Yongzhi
    [J]. EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY, 2019, 21 (03): : 403 - 410
  • [10] Vibration signal analysis for gear fault diagnosis with various crack progression scenarios
    Mohammed, Omar D.
    Rantatalo, Matti
    Aidanpaa, Jan-Olov
    Kumar, Uday
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2013, 41 (1-2) : 176 - 195
12345