Fault diagnosis for supporting rollers of the rotary kiln using the dynamic model and empirical mode decomposition

被引:2
|
作者
Zheng, Kai [1 ]
Zhang, Yun [1 ]
Zhao, Chen [1 ]
Li, Tianliang [1 ]
机构
[1] Wuhan Univ Technol, Sch Mech & Elect Engn, Wuhan 430070, Peoples R China
来源
MECHANIKA | 2016年 / 03期
关键词
Supporting rollers; fault diagnosis; numerical analysis; empirical mode decomposition; vibration monitoring; HILBERT SPECTRUM; EXTRACTION; MACHINERY;
D O I
10.5755/j01.mech.22.3.13072
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
Rotary kiln is key equipment widely used in the cement, metallurgical and environmental protection industry. The operation state of the rotary kiln was largely determined by the working condition of supporting rollers. This paper models the vibration mechanism of the supporting rollers under the rotary kiln crank caused by the internal thermal process. Based on the numerical analysis, a methodology based on empirical mode decomposition (EMD) for the fault diagnosis of the supporting rollers was proposed. By using EMD, the complicated vibration signal of the kiln can be decomposed into a number of intrinsic mode functions (IMFs). An analysis was made over the energy moment of IMF components to indicate the energy variation of the kiln harmonic and the roller harmonic of the vibration signals. Simulation and in field experiment results proved that the proposed method provided a validity of the approach for the condition monitoring and fault diagnosis of the low-speed machinery like the rotary kiln.
引用
收藏
页码:198 / 205
页数:8
相关论文
共 50 条
  • [41] Fault diagnosis of a machine tool rotary axis based on a motor current test and the ensemble empirical mode decomposition method
    Zhao, F.
    Mei, X.
    Tao, T.
    Jiang, G.
    Zhou, Y.
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2011, 225 (C5) : 1121 - 1129
  • [42] Fine-tuned variational mode decomposition for fault diagnosis of rotary machinery
    Dibaj, Ali
    Ettefagh, Mir Mohammad
    Hassannejad, Reza
    Ehghaghi, Mir Biuok
    STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2020, 19 (05): : 1453 - 1470
  • [43] Dynamic simulation model of rotary lime kiln
    Karhela, T
    Lappalainen, J
    Peltola, H
    Juslin, K
    INTERNATIONAL CHEMICAL RECOVERY CONFERENCE, VOLS 1-3, 1998, : 1081 - 1093
  • [44] Fault diagnosis of rotating machinery based on noise reduction using empirical mode decomposition and singular value decomposition
    Jiang, Fan
    Zhu, Zhencai
    Li, Wei
    Zhou, Gongbo
    Chen, Guoan
    JOURNAL OF VIBROENGINEERING, 2015, 17 (01) : 164 - 174
  • [45] Application of Ensemble Empirical Mode Decomposition to Diagnosis Bladed Disk Fault
    Bouhali, Rima
    Tadjine, Kamel
    Saadi, Mohamed Nacer
    Bandjama, Hocine
    PROCEEDINGS OF 2016 8TH INTERNATIONAL CONFERENCE ON MODELLING, IDENTIFICATION & CONTROL (ICMIC 2016), 2016, : 332 - 337
  • [46] Empirical Mode Decomposition for Fault Diagnosis of Multi-Component Systems
    Syan, Chanan S.
    Ramsoobag, Geeta
    2018 ANNUAL RELIABILITY AND MAINTAINABILITY SYMPOSIUM (RAMS), 2018,
  • [47] Gear fault diagnosis based on order tracking and empirical mode decomposition
    Kang, Hai-Ying
    Luan, Jun-Ying
    Zheng, Hai-Qi
    Cui, Qing-Bin
    Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University, 2007, 41 (09): : 1529 - 1532
  • [48] Gearbox fault diagnosis and prediction based on empirical mode decomposition scheme
    Wang, Jia-Zhong
    Zhou, Gui-Hong
    Zhao, Xiao-Shun
    Liu, Shu-Xia
    PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2007, : 1072 - 1075
  • [49] Gearbox Fault Diagnosis Based on Empirical Mode Decomposition and Hilbert Transform
    Liu, Yanli
    Zhang, Dexiang
    Ji, Mingwei
    AUTOMATIC MANUFACTURING SYSTEMS II, PTS 1 AND 2, 2012, 542-543 : 238 - +
  • [50] Noise Eliminated Ensemble Empirical Mode Decomposition for Bearing Fault Diagnosis
    Faysal, Atik
    Ngui, Wai Keng
    Lim, M. H.
    JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES, 2021, 9 (08) : 2229 - 2245