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Fault Diagnosis of Broken Rotor Bars Based on the Steady-state Stator Current

Author: LiHongXia
Tutor: YeDaPeng;ZhangXiang
School: Fujian Agriculture and Forestry University
Course: Mechanical Design and Theory
Keywords: Broken rotor bars Hilbert transform Fault diagnosis Wavelet packet decomposition Stator current analysis
CLC: TM346
Type: Master's thesis
Year: 2009
Downloads: 103
Quote: 1
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Abstract


Induction motor is widely used in industrial areas for its simple structure, low cost, small amount of maintenance. However, with the rapid development of the modern industrial system, the capacity of single motor increases gradually, and the load becomes more and more complex, which cause that fault often occurs during motor operation. The motor failure will not only damage the motor itself, but also make the motor disabled and result in the collapse of the production line, which causes huge economic losses and disastrous consequences. Studies show that induction motor broken rotor broken bars fault is a main type of the failures, with a percentage of 5% -10% of the total failures. So the correct diagnosis of the broken rotor bars fault has a great significance on the industrial production.This paper discuss the principle of fault diagnosis of broken rotor bars and describes that there are some characteristics appear in the steady-state stator current when it has broken bars faults. The steady-state stator current simulation models for different noise level are established by assigning steady-state stator current as analysis object. Firstly, the stator current is made by Hilbert-transform, and then the DC component is removed by using double Hilbert-transform. Thirdly, the features are extracted by applying 3 levels wavelet packet decomposition. Finally the faults are identified by using BP neural network. The simulation results show that: the recognition rate exceed 90% by using Hilbert and wavelet packet combination in different noise level.A fault diagnosis experimental system is built for broken rotor bars by setting the J02-12-2 induction motor as the research object and using the signal acquisition instrument INV306U intelligent platform in the paper. The steady-state stator current data are collected for broken and normal mode rotor in this experiment. Combining application of VC + +6.0 and Matlab engine, comparison analysis is achieved through time domain, frequency domain, wavelet packet, and Hilbert and wavelet packet combination. Experimental results show that: the rotor broken bar recognition rate is up to 92.5% by using Hilbert and wavelet packet combining method.

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CLC: > Industrial Technology > Electrotechnical > Motor > AC motor > Induction motor
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