Study on the recursion neural network method with the deviation unit applied to fault diagnosis of armored vehicle gearbox

被引：0
|
作者：
Yao Zhuting [1 ]
Pan Hongxia [1 ]
机构：
[1] N Univ China, Coll Mech Engn & Automatizat, Taiyuan 030051, Peoples R China
来源：
ISTM/2007: 7TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-7, CONFERENCE PROCEEDINGS | 2007年
关键词：
gearbox; neural network; and 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：
On the basis of introducing the BP neural network and its shortage, the paper put forward the recursion neural network method with deviation unit and applied it to the fault diagnosis of armored vehicle gearbox. By setting the fault to gear which is the basic parts of the gearbox, the validity of arithmetic applied to fault diagnosis of the armored vehicle gearbox is studied on the improved arithmetic of the BP neural network and the recursion neural network method with the deviation unit. The research enunciates the recursion neural network method with the deviation unit compares BP neural network with quick training speed, high accuracy, save time, accurate fault fix position.
引用
收藏
页码：2721 / 2724
页数：4
相关论文
共 50 条
  • [21] Gearbox fault diagnosis method based on deep convolutional neural network vibration signal image recognition
    Bian Jingyi
    Liu Xiuli
    Xu Xiaoli
    PROCEEDINGS OF 2019 14TH IEEE INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS (ICEMI), 2019, : 456 - 465
  • [22] Application of Feature Fusion Based on DHMM Method and BP Neural Network Algorithm in Fault Diagnosis of Gearbox
    Zhu, Wen-hui
    Huang, Jin-ying
    Feng, Shun-xiao
    Wei, Jie-jie
    Chen, Hai-xia
    2017 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-HARBIN), 2017, : 449 - 453
  • [23] Fault diagnosis method of planetary gearbox based on enhanced capsule network
    Li D.-C.
    Zhang M.
    Wang K.-S.
    Xiang H.-B.
    Rang T.-B.
    Wang Y.-G.
    Kongzhi yu Juece/Control and Decision, 2023, 38 (03): : 661 - 669
  • [24] IMPROVING PERFORMANCE OF AN ARTIFICIAL NEURAL NETWORK BASED GEARBOX FAULT DIAGNOSIS SYSTEM
    Hajnayeb, Ali
    Ghasemloonia, Ahmad
    Khadem, Siamak Esmaeelzadeh
    Moradi, Mohammad Hasan
    PROCEEDINGS OF THE ASME 10TH BIENNIAL CONFERENCE ON ENGINEERING SYSTEMS DESIGN AND ANALYSIS, 2010, VOL 2, 2010, : 323 - 328
  • [25] Study on SOM Neural Network Applied to the Fault Diagnosis of Hoist Brake System
    Lei, Yong-Tao
    INTERNATIONAL CONFERENCE ON CONTROL ENGINEERING AND AUTOMATION (ICCEA 2014), 2014, : 165 - 168
  • [26] An automatic speed adaption neural network model for planetary gearbox fault diagnosis
    Chen, Peng
    Li, Yu
    Wang, Kesheng
    Zuo, Ming J.
    MEASUREMENT, 2021, 171
  • [27] Fault Diagnosis algorithm of Wind Power Gearbox Based on Fuzzy Neural Network
    Bai, Ruifei
    Zhang, Wei
    Zhao, Doudou
    PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019), 2019, : 3291 - 3296
  • [28] The intelligent fault diagnosis of wind turbine gearbox based on artificial neural network
    Yang, Shulian
    Li, Wenhai
    Wang, Canlin
    PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON CONDITION MONITORING AND DIAGNOSIS, 2007, : 1327 - +
  • [29] Applied study of electromotor fault diagnosis based on wavelet packets and neural network
    Hou, Bei-Ping
    Zhu, Wen
    Xiang, Xin-Jian
    Shang, Xing-Yao
    PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2006, : 2912 - +
  • [30] Fault Diagnosis of Planetary Gearbox Based on Signal Denoising and Convolutional Neural Network
    Sun, Guodong
    Wang, Youren
    Sun, Canfei
    2019 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-PARIS), 2019, : 96 - 99
12345