Shaft orbit analysis Based on LabVIEW for Fault Diagnosis of Rotating Machinery

被引:0
|
作者
Zhang, Hong-xin [1 ]
Wang, Ming-zhu [1 ]
Li, He [1 ]
Shi, Xian-jiang [1 ]
机构
[1] Harbin Univ Sci & Technol, Inst Machine Intelligence, Harbin, Heilongjiang, Peoples R China
关键词
Fault diagnosis; Pattern recognition; Shaft orbits; LabVIEW;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
A method of axis orbit analysis based on LabVIEW is researched in order to recognize the fault of rotating machinery. A rotor fault diagnosis system including a fault simulation platform, a set of testing devices and a signal analysis program is developed. The signal analysis program can be used to realize some functions such as data acquisition, signal analysis, processing and display, pattern recognition and fault diagnosis. With this program the fault diagnosis system can be operated to automatically measure and identify the shaft orbit of a rotor and get fault results, which the key principle is on the basis of the invariant moment algorithm for pattern recognition. The experimental results show that the shaft orbit of a rotor can be synthesized and identified through the invariant moment calculation. Because the shape of the shaft orbit of the rotor is close to an ellipse shape the fault result is imbalance. This study is helpful to develop an online fault diagnosis system based on LabVIEW for the fault diagnosis of rotating machinery.
引用
收藏
页码:972 / 975
页数:4
相关论文
共 50 条
  • [21] Fault detection and diagnosis of rotating machinery
    Loparo, KA
    Adams, ML
    Lin, W
    Abdel-Magied, MF
    Afshari, N
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2000, 47 (05) : 1005 - 1014
  • [22] Fault detection and diagnosis in rotating machinery
    Loparo, KA
    Afshari, N
    Abdel-Magied, M
    1998 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5, 1998, : 2986 - 2991
  • [23] The Study of Fault Diagnosis in Rotating Machinery
    Othman, Nor Azlan
    Damanhuri, Nor Salwa
    Kadirkamanathan, Visakan
    CSPA: 2009 5TH INTERNATIONAL COLLOQUIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, PROCEEDINGS, 2009, : 69 - 74
  • [24] Analysis of experiment result and fault diagnosis for aeroengine rotating shaft
    Zhao Baoqun
    Wang Yuanyang
    SEVENTH INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION AND CONTROL TECHNOLOGY: SENSORS AND INSTRUMENTS, COMPUTER SIMULATION, AND ARTIFICIAL INTELLIGENCE, 2008, 7127
  • [25] Element analysis and its application in rotating machinery fault diagnosis
    Dai, Hanfang
    Wang, Yanxue
    Wang, Xuan
    Liu, Qi
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2023, 34 (02)
  • [26] Segmented infrared image analysis for rotating machinery fault diagnosis
    Duan, Lixiang
    Yao, Mingchao
    Wang, Jinjiang
    Bai, Tangbo
    Zhang, Laibin
    INFRARED PHYSICS & TECHNOLOGY, 2016, 77 : 267 - 276
  • [27] Application of Rotating Machinery Fault Diagnosis Based on Deep Learning
    Cui, Wei
    Meng, Guoying
    Wang, Aiming
    Zhang, Xinge
    Ding, Jun
    SHOCK AND VIBRATION, 2021, 2021
  • [28] Feature Denoising-based Fault Diagnosis for Rotating machinery
    Hq, Qin
    Si, Xiao-Sheng
    Lv, Yun-Rong
    2020 35TH YOUTH ACADEMIC ANNUAL CONFERENCE OF CHINESE ASSOCIATION OF AUTOMATION (YAC), 2020, : 284 - 287
  • [29] Fault diagnosis of rotating machinery based on SVD, FCM and RST
    Ru-qiang Li
    Jin Chen
    Xing Wu
    Alfayo A. Alugongo
    The International Journal of Advanced Manufacturing Technology, 2005, 27 : 128 - 135
  • [30] Fault diagnosis of rotating machinery based on vector ambiguity function
    Shandong University, Jinan 250061, China
    不详
    Zhongguo Jixie Gongcheng, 2006, SUPPL. 2 (74-77):