Holographic Spectrum in the Remote Rotating Machinery Fault Diagnosis

被引:1
|
作者
Tang, WuChu [1 ,2 ]
Shi, ZhiHui [1 ]
Kang, DaLi [3 ]
机构
[1] Dalian JiaoTong Univ, Sch Mech Engn, Dalian 116028, Peoples R China
[2] Dalian Univ Technol, Sch Mech Engn, Dalian 116024, Peoples R China
[3] Dalian Shenglilai Monitoring Tech Corp, Dalian 116024, Peoples R China
来源
MECHANICAL AND ELECTRONICS ENGINEERING III, PTS 1-5 | 2012年 / 130-134卷
关键词
Rotating machinery; Fault diagnosis; Holographic spectrum; MD-Base database;
D O I
10.4028/www.scientific.net/AMM.130-134.2836
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
In this paper, a remote real-time online rotating machinery monitoring system, which was developed and tested in the Industrial application, is presented including its remote monitoring sub-system, fault diagnosis sub-system. First, the system architecture is introduced. Next, a web-based remote monitoring system is designed, which allows researches and engineers to remotely monitor the health of the machine from any remote geographic location through the Internet. Finally, the holographic spectrum technology in this system is discussed as well for the purpose of providing accurate and reliable diagnosis of the machine states and accident prevention.
引用
收藏
页码:2836 / +
页数:2
相关论文
共 50 条
  • [1] RESEARCH ON HAAR SPECTRUM IN FAULT DIAGNOSIS OF ROTATING MACHINERY
    徐尹格
    颜玉玲
    Applied Mathematics and Mechanics(English Edition), 1991, (01) : 61 - 66
  • [2] 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
  • [3] Cumulative spectrum distribution entropy for rotating machinery fault diagnosis
    Wang, Shun
    Li, Yongbo
    Noman, Khandaker
    Wang, Dong
    Feng, Ke
    Liu, Zheng
    Deng, Zichen
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2024, 206
  • [4] Complex Singular Spectrum Decomposition and Its Application to Rotating Machinery Fault Diagnosis
    Pang, Bin
    Tang, Guiji
    Tian, Tian
    IEEE ACCESS, 2019, 7 : 143921 - 143934
  • [5] Neurofuzzy methodologies for rotating machinery fault diagnosis
    Yan, T
    Rong, CJ
    ISTM/2005: 6th International Symposium on Test and Measurement, Vols 1-9, Conference Proceedings, 2005, : 1061 - 1063
  • [6] A review of fault diagnosis methods for rotating machinery
    Shi, Zhenjin
    Li, Yueyang
    Liu, Shuai
    2020 IEEE 16TH INTERNATIONAL CONFERENCE ON CONTROL & AUTOMATION (ICCA), 2020, : 1618 - 1623
  • [7] A method for intelligent fault diagnosis of rotating machinery
    Chen, CZ
    Mo, CT
    DIGITAL SIGNAL PROCESSING, 2004, 14 (03) : 203 - 217
  • [8] A new fault diagnosis method of rotating machinery
    Chen, Chih-Hao
    Shyu, Rong-Juin
    Ma, Chih-Kao
    SHOCK AND VIBRATION, 2008, 15 (06) : 585 - 598
  • [9] A Novel Method for Fault Diagnosis of Rotating Machinery
    Tang, Meng
    Liao, Yaxuan
    Luo, Fan
    Li, Xiangshun
    ENTROPY, 2022, 24 (05)
  • [10] Rotating machinery fault diagnosis based on multiple fault manifolds
    Su, Zu-Qiang
    Tang, Bao-Ping
    Zhao, Ming-Hang
    Qin, Yi
    Zhendong Gongcheng Xuebao/Journal of Vibration Engineering, 2015, 28 (02): : 309 - 315