Support vector machine for fault diagnosis of the broken rotor bars of squirrel-cage induction motor

2009 ◽  
Vol 19 (4) ◽  
pp. 557-564 ◽  
Author(s):  
Jaroslaw Kurek ◽  
Stanislaw Osowski
2014 ◽  
Vol 6 ◽  
pp. 849670 ◽  
Author(s):  
Zhike Zhao ◽  
Xin Wang ◽  
Xiaoguang Zhang

This paper is to propose a novel fault diagnosis method for broken rotor bars in squirrel-cage induction motor of hoister, which is based on duffing oscillator and multifractal dimension. Firstly, based on the analysis of the structure and performance of modified duffing oscillator, the end of transitional slope from chaotic area to large-scale cycle area is selected as the optimal critical threshold of duffing oscillator by bifurcation diagrams and Lyapunov exponent. Secondly, the phase transformation duffing oscillator from chaos to intermittent chaos is sensitive to the signals, whose frequency difference is quite weak from the reference signal. The spectrums of the largest Lyapunov exponents and bifurcation diagrams of the duffing oscillator are utilized to analyze the variance in different parameters of frequency. Finally, this paper is to analyze the characteristics of both single fractal (box-counting dimension) and multifractal and make a comparison between them. Multifractal detrended fluctuation analysis is applied to detect extra frequency component of current signal. Experimental results reveal that the method is effective for early detection of broken rotor bars in squirrel-cage induction motor of hoister.


2014 ◽  
Vol 577 ◽  
pp. 726-734
Author(s):  
Hong Yu Zhu ◽  
Jing Tao Hu ◽  
Lei Gao ◽  
Hao Huang

A new method has been developed for the detection of broken rotor bars fault in squirrel cage induction motor during startup regimes. The incipient detection of fault is made by using DWT analysis of FIR low pass filtered original startup transient current signal. The extracted particular characteristic evolution of the time-varying signal is used as a fault index. The method was tested using healthy and damaged 3.0kW squirrel cage induction motors under no-load conditions. The results indicate that the method yields a high degree of performance in fault identification.


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