Research On Fault Diagnosis Method Of Frequency Converter Main Circuit Based On Matlab

The frequency converter has excellent speed regulation function,high efficiency of braking and good energy saving effect,and has been widely developed and applied at home and abroad in recent years.However,the working environment of the inverter often has a bad environment,which may easily cause the inverter to malfunction.In the event of a fault in the frequency converter,production will stop,and in severe cases,it will cause casualties and major economic losses.At present,the methods for fault diagnosis of the main circuit of the inverter have certain limitations,and the complexity of the system cannot be completely solved effectively.This paper proposes a fault diagnosis method for the main circuit of the inverter based on Matlab fault simulation to diagnose the main circuit fault of the inverter.First of all,this paper analyzes the main circuit structure and fault mechanism of the inverter,and finds the main cause of the main circuit failure.Since the establishment of the fault model requires a large number of fault samples,this paper uses the Simulink toolbox under Matlab software to build the main circuit simulation model of the inverter.According to the main circuit fault mechanism,the simulation model is used to simulate the faults that may occur during the working process.Second,the wavelet packet analysis method is used to analyze the simulated main circuit fault of the inverter,and the three-phase output when the inverter is faulty is used as the fault information to collect the fault samples.The wavelet packet analysis is used to extract the characteristic coefficients that can characterize the fault signal.Construct a feature vector.In this paper,Matlab circuit simulation,wavelet packet analysis,BP neural network and genetic algorithm are applied to the fault diagnosis of frequency converter.It solves the problem that the inverter is difficult to diagnose accurately and quickly in the event of a fault,and provides an effective method for fault diagnosis of the inverter,which can effectively improve the safety of the inverter and reduce the maintenance cost and time of the inverter.The stability of production operations.Finally,the feature vector extracted by wavelet packet analysis is used as the input of the neural network,and the fault result of the inverter is used as the output of the neural network to construct the BP neural network model.The fault is located through the neural network to solve the complex relationship between the fault feature and the fault result.In order to obtain better diagnostic performance,the BP neural network is easy to fall into the local extremum and the accuracy of the model diagnosis is not high.This paper uses the genetic algorithm to optimize the established fault diagnosis model of the inverter.The test results show that the optimized the model is more accurate.In this paper,Matlab circuit simulation,wavelet packet analysis,BP neural network and genetic algorithm are applied to the fault diagnosis of frequency converter.It solves the problem that the inverter is difficult to diagnose accurately and quickly in the event of a fault,and provides an effective method for fault diagnosis of the inverter,which can effectively improve the safety of the inverter and reduce the maintenance cost and time of the inverter.The stability of production operations.