The Research Of OMAP-L138 Based Detection System For Rotor Bar Fault In Three-phase Asynchronous Motors

The 70% of power source is come from AC asynchronous motor in modern industrial production.There are three mainstream types of motor: short-circuit between the turns of the coils?bearing fault and broken rotor bar.This paper's research is based on the rotor broken bar fault of three phase asynchronous AC motor,devoted myself to exploitation and designing an embedded detection system,which be applied to detect rotor broken bar fault of three-phase asynchronous ac motor.The research is mainly get down from two aspects,the research of sensitive and reliable detection methods and the development of rotor fault detection equipment.In the aspect of detection algorithm,there are two difficulties in detecting the BRB of the induction motors.In terms of rotor fault detection,in view of the contradiction between the resolution of the FFT algorithm and sampling time,this paper applied spatial spectrum estimation technique to estimate the frequency of the fault feature component,and combined with optimization algorithm to estimate the features of amplitude.In the first place,A new method for detecting broken rotor bar fault(BRB)in induction motors is proposed which is based on the combination of streamlined fourth-order cumulants,Multiple Signal Classification(MUSIC)and hybrid genetic algorithm.MUSIC based on fourth-order cumulants can effectively reduce the noise interference,extend signal array,improve spectral estimation performance and hence,extract BRB feature component and power frequency component with a high frequency resolution;and then try to apply the Hybrid Genetic algorithm to determine the amplitude and the initial phase of each frequency component.Additionally,in order to speed up MUSIC based on fourth-order cumulants,a reduction algorithm is proposed to eliminate redundant data of the matrix according to the composition method of fourth-order cumulants matrices,thus greatly reducing the calculation amount of this kind of MUSIC.To cope with the premature and slow convergent rate,a global optimization method is presented in this paper,which shares the advantages of both genetic and simples.A series of simulations and experiments are conducted to verify the presented detection method's high spectral resolution and estimation precision in the low SNR and short sampling time.Secondly,This paper presents a detection method for rotor fault in induction motors,which combines the estimation of signal parameters via rotational invariance technique(ESPRIT)and Prony algorithm.With the high frequency resolution characteristic,the ESPRIT can precisely extract the broken rotor bar fault feature frequency components and the others in stator current signals.However,it can not estimate the amplitudes and initial phases accurately.And then try to apply the extended Prony algorithm to determine the amplitude and the initial phase of each frequency component.The simulation and experimental results demonstrate that these two methods are effectively and suitable for online detection due to its simple algorithm and short runtime.In the research field of detection equipment,scheme of monitoring system rotor fault in induction motors is designed and implemented.The development process of man-machine conversation interface,data acquisition module and dual-kernel communication mechanism is described in detail in both hardware and software way.Man-machine conversation interface is exploited by Qt software,signal acquisition function is based on ADS8556 chip,the dual-kernel data communication mechanism is developed based on shared memory,whose key part includes hardware initialization and driver,communication synchronization and communication protocol.This system makes good use of the advantages of OMAP dual-kernel,on one hand ARM is mainly used to control the hardware resources and dispatch task,on the other hand DSP is mainly used for data processing and other real-time tasks.The experimental had been carried out in order to test the performance of data acquisition and dual-kernel communication,whose results showed that the system could satisfied the requirements of reliability and real-time performance of motor fault detection.