Angular-based modeling of induction motors for monitoring

被引:7
|
作者
Fourati, Aroua [1 ,2 ]
Bourdon, Adeline [1 ]
Feki, Nabih [2 ]
Remond, Didier [1 ]
Chaari, Fakher [2 ]
Haddar, Mohamed [2 ]
机构
[1] Univ Lyon, INSA Lyon, CNRS, LaMCoS,UMR 5259, 20 Rue Sci, F-69621 Villeurbanne, France
[2] Minist Higher Educ & Res Tunisia, Natl Engn Sch Sfax, Lab Mech Modelling & Mfg, LA2MP, BP 1173, Sfax 3038, Tunisia
关键词
Angular approach; rotating-machinery diagnosis; Motor Current Signal Analysis (MCSA); electromagnetic-mechanical modeling; Permeance Network Model (PNM); FAULT-DETECTION; STATOR CURRENT; DIAGNOSIS; ECCENTRICITY; VIBRATION; MACHINES;
D O I
10.1016/j.jsv.2016.12.031
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Understanding the occurrence of bearing defects in electrical current signals using Motor Current Signal Analysis (MCSA) requires the implementation of numerical models. In this paper, an electro-magnetic-mechanical model is proposed to describe the dynamic behavior of a squirrel cage induction motor coupled to a rotating shaft supported by elastic foundations. The aim of this research work is to gain understanding of the interaction between multiphysics subsystems, mainly in faulty cases, to decipher the transfer path from the defect to its manifestation in stator currents. A new method of writing dynamic equations for simplified simulations of an induction motor is developed using an angular approach. In addition to its capacity to extend the modeling to non-stationary operating conditions, the model proposed highlights the angular periodicity of the rotating motor's geometry. The electromagnetic field of the motor is redistributed periodically when a geometric defect occurs on a rotating part of the global system. In this case, the electromagnetic torque of the induction motor may present angularly-periodic variations. After having presented the electromagnetic-mechanical coupling methodology, the influence of torque variations is investigated and the importance of the angle-time function is highlighted. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:371 / 392
页数:22
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