Vibration fault signal analysis and diagnosis of flue gas turbine

被引:0
|
作者
Xiong, Huiying [1 ]
Peng, Yiheng [2 ]
Hu, Yiyang [3 ]
Zhang, Lin [3 ]
Li, Ying [4 ]
机构
[1] Department of Information and Mechanical and Electrical Engineering, Guangxi Agricultural Vocational and Technical College, Nanning,530007, China
[2] College of Information Science and Technology, Ocean University of China, Qingdao,266100, China
[3] School of Mechanical Engineering and Rail Transit, Changzhou University, Changzhou,213164, China
[4] Hunan Chemical Vocational Technology College, Hunan,414011, China
关键词
Fault detection - Condition monitoring - Vibration analysis - Flues - Gas turbines - Flue gases;
D O I
暂无
中图分类号
学科分类号
摘要
Flue gas turbine is a kind of typical rotating machinery. It uses the flue gas expansion which contains a lot of heat energy and pressure energy generated in the catalytic cracking process to drive the axial-flow compressor or generator to rotate. Due to the complex structure, bad operating environment, poor stability, and large vibration of the flue gas turbine, its failure rate is high, which causes immeasurable economic losses and safety hazards. Therefore, how to effectively obtain, extract and identify the fault information of flue gas turbine is a difficult problem in the field of fault diagnosis technology. In this paper, aiming at two kinds of faults in the tp9-90 flue gas turbine system, i.e., rotor misalignment and unbalance causing excessive vibration, the corresponding geometric model and mathematical model are established, and the fault mechanism is revealed. Through on-line monitoring of flue gas turbine rotor vibration signal, the running state of flue gas turbine is comprehensively analyzed, and the technological transformation is carried out according to the fault causes, the improved flue gas machine runs smoothly, and the vibration and failure rate are obviously reduced. This study provides an important reference for condition monitoring and fault diagnosis of flue gas turbines. © 2021
引用
下载
收藏
相关论文
共 50 条
  • [41] Fault diagnosis system of rotating machinery vibration signal
    You, Lei
    Hu, Jun
    Fang, Fang
    Duan, Lintao
    CEIS 2011, 2011, 15
  • [42] Fault Diagnosis of Wind Turbine Gearbox Based on Vibration Data
    Wang, Hongwei
    Wang, Zeyuan
    Liu, Wei
    2018 IEEE 15TH INTERNATIONAL CONFERENCE ON E-BUSINESS ENGINEERING (ICEBE 2018), 2018, : 234 - 238
  • [43] Vibration monitoring and fault diagnosis system of turbine-generator
    Dongmei, Du
    Qing, He
    Hong, Li
    PROCEEDINGS OF THE ASME POWER CONFERENCE 2007, 2007, : 275 - 278
  • [44] Application of iterative singular value decomposition de-noising to flue gas turbine signal analysis
    Wang Hao
    Zhang Laibin
    Wang Zhaohui
    ENGINEERING STRUCTURAL INTEGRITY: RESEARCH, DEVELOPMENT AND APPLICATION, VOLS 1 AND 2, 2007, : 1138 - 1140
  • [45] Gas Turbine Fault Diagnosis using Random Forests
    Maragoudakis, Manolis
    Loukis, Euripides
    Pantelides, Panayotis-Prodromos
    ECAI 2008, PROCEEDINGS, 2008, 178 : 769 - +
  • [46] Neural network technique for gas turbine fault diagnosis
    Ogaji, SOT
    Singh, R
    ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS, 2002, 10 (04): : 209 - 214
  • [47] Fault diagnosis and isolation in aircraft gas turbine engines
    Sarkar, Soumik
    Mukherjee, Kushal
    Ray, Asok
    Yasar, Murat
    2008 AMERICAN CONTROL CONFERENCE, VOLS 1-12, 2008, : 2166 - 2171
  • [48] HYBRID FAULT DIAGNOSIS: APPLICATION TO A GAS TURBINE ENGINE
    Mohammadi, Rasul
    Hashtrudi-Zad, Shahin
    Khorasani, Khashayar
    PROCEEDINGS OF THE ASME TURBO EXPO 2009, VOL 1, 2009, : 719 - 729
  • [49] Redundant Graph to Improve Fault Diagnosis in a Gas Turbine
    Verde, C.
    Sanchez-Parra, Marino
    2010 CONFERENCE ON CONTROL AND FAULT-TOLERANT SYSTEMS (SYSTOL'10), 2010, : 215 - 220
  • [50] Neural network technique for gas turbine fault diagnosis
    Ogaji, S.O.T.
    Singh, R.
    International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications, 2002, 10 (04): : 209 - 214