Stator Current Bi-Spectrum Patterns for Induction Machines Multiple-Faults Detection

被引:0
作者
Saidi, L. [1 ]
Fnaiech, F. [1 ]
Capolino, G-A [2 ]
Henao, H. [2 ]
机构
[1] Univ Tunis, Ecole Super Sci & Tech Tunis, 5 Ave Taha Hussein, Tunis 1008, Tunisia
[2] Univ Picardie Jules Verne, Dept Elect Engn, F-80000 Amiens, France
来源
38TH ANNUAL CONFERENCE ON IEEE INDUSTRIAL ELECTRONICS SOCIETY (IECON 2012) | 2012年
关键词
Bearings; bi-spectrum analysis; receiver operating characteristics (ROC); rotor broken bars; higher order spectra; multiple-fault diagnosis; ROLLING ELEMENT BEARINGS; CYCLIC BISPECTRUM; DIAGNOSIS;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Inspecting the literature, the most used techniques proposed for induction machines diagnosis are focused on detecting single faults. There is a lack of works dealing with the diagnosis and identification of multiple combined faults. In this framework, this paper presents the stator current bi-spectrum analysis to detect two types of faults mixed together which may appear in three phase induction motors. Based on real experimental data, the detection study concerns isolated rotor broken bars and damage in the bearing's inner race rolling element. For multiple faults detection, and for lack of experimental data, only synthetic data are used. To deal with the frequency analysis, a mathematical model of the stator current has been derived and used into the bi-spectrum formulas. The main contribution of this paper is the development of a theoretical method which may help the user to assess the presence of fault frequencies in induction motors in both settings namely single or multiple combined faults. To highlight the superiority of the bi-spectrum tool over the spectrum, receiver operating characteristics (ROC) analysis has been carried out. Therefore, simulation results are performed in noisy environment showing that the bi-spectrum is able to detect frequency faults better.
引用
收藏
页码:5132 / 5137
页数:6
相关论文
共 22 条
  • [1] Detection of combined faults in induction machines with stator parallel branches through the DWT of the startup current
    Antonino-Daviu, J.
    Rodriguez, P. Jover
    Riera-Guasp, M.
    Pineda-Sanchez, M.
    Arkkio, A.
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2009, 23 (07) : 2336 - 2351
  • [2] Ayhan B., P IEEE ISIE SPAIN JU, P1080
  • [3] Ballal M. S., 1999, IEEE IND ELECT, V54, P250
  • [4] Bellini Alberto, 2008, IECON 2008 - 34th Annual Conference of IEEE Industrial Electronics Society, P3079, DOI 10.1109/IECON.2008.4758452
  • [5] Advances in Diagnostic Techniques for Induction Machines
    Bellini, Alberto
    Filippetti, Fiorenzo
    Tassoni, Carta
    Capolino, Gerard-Andre
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2008, 55 (12) : 4109 - 4126
  • [6] Models for bearing damage detection in induction motors using stator current monitoring
    Bloedt, Martin
    Granjon, Pierre
    Raison, Bertrand
    Rostaing, Gilles
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2008, 55 (04) : 1813 - 1822
  • [7] Application of the bispectrum for detection of small nonlinearities excited sinusoidally
    Courtney, C. R. P.
    Neild, S. A.
    Wilcox, P. D.
    Drinkwater, B. W.
    [J]. JOURNAL OF SOUND AND VIBRATION, 2010, 329 (20) : 4279 - 4293
  • [8] An introduction to ROC analysis
    Fawcett, Tom
    [J]. PATTERN RECOGNITION LETTERS, 2006, 27 (08) : 861 - 874
  • [9] The Application of High-Resolution Spectral Analysis for Identifying Multiple Combined Faults in Induction Motors
    Garcia-Perez, Arturo
    de Jesus Romero-Troncoso, Rene
    Cabal-Yepez, Eduardo
    Alfredo Osornio-Rios, Roque
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2011, 58 (05) : 2002 - 2010
  • [10] A New Bearing Fault Detection Method in Induction Machines Based on Instantaneous Power Factor
    Ibrahim, Ali
    El Badaoui, Mohamed
    Guillet, Francois
    Bonnardot, Ferderic
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2008, 55 (12) : 4252 - 4259