Study On Diagnosis Method Of Broken Rotor Bar Fault For Induction Motors With Various Load Torque

Induction motors play an important role in actual production,and its safe and efficient operation is also very crucial.And according to the statistics,broken rotor bar fault is the most common fault of induction motors.At present,the detection method of rotor fault for induction motors with constant load torque is relatively mature,however the detection method of rotor fault for induction motors with various load torque is less.Hence,research on diagnosis method of broken rotor bar fault for induction motor with various load torque including time-varying load torque(load torque increases from no-load to full-load with time)and oscillating load torque(oscillation load is composed of a constant load and a oscillating load with a single-frequency sine wave)is the focus content of this paper.The main contributions are presented as follows.(1)Analyzing the mathematical model of induction motors including healthy motor and broken rotor bar fault motor on the basis of multi-loop model,and the mechanism of broken rotor bar fault is expounded,which provides a theoretical basis for further research for rotor fault detection of induction.(2)A detection method of broken rotor bar fault for induction motor with time-varying load torque is proposed,which is based on Hankel-SVD and wavelet packet decomposition(WPT)algorithm.Firstly,Hanke-SVD is a superior filtering technique,which can eliminate interference of the fundamental component from the stator current of induction motor to highlight the characteristic components.Then Decomposing the stator current without fundamental component through WPT,and extracting the energy of different frequency band.Finally,constituting the feature vector of the frequency band energy including rotor fault characteristic frequency.As a result,the experiment reminds the effectiveness of the proposed method.(3)A novel approach to detect broken rotor bar fault motor with oscillating load torque is illustrated,which is combining instantaneous power with WPT.Moreover,the diagnosis criteria of rotor fault with oscillating load torque is established.Firstly,instantaneous power can distinguish the broken rotor bar fault and the load oscillation because of the effect of the broken rotor bar fault and load oscillation on instantaneous reactive power and instantaneous active power is totally different.Then instantaneous reactive power and instantaneous active power are decomposed into different frequency band and calculating the energy of different frequency band,Finally,extracting the energy of frequency band including rotor fault and load oscillation characteristic frequency as the feature vectors of fault diagnosis.As a result,the experiment reminds the effectiveness of the proposed method.(4)Based on fault feature extracted through the method proposed in chapter 3 and chapter 4,a novel method to identify broken rotor bar fault on the basis of ensemble classifier(EC)is proposed.According to ensemble learning,BP neural network,support vector machine(SVM)and random forests(RF)are combined through Bagging algorithm,which identify broken rotor bar faults in induction motors accurately and rapidly.Finally,the simulation data and experimental data illustrate the effectiveness of the proposed method.