Analysis And Processing Technology Of EMC Test Data Based On Wavelet Transform

As the integration level of electronic systems increases steadily,the electromagnetic environment in which the system is located is becoming more and more complex,and this is generating many electromagnetic compatibility problems.In order to solve these problems,the traditional electromagnetic compatibility fault diagnosis technology have to firstly perform a series of electromagnetic compatibility tests on the system,then analyze the test data,and finally locate the fault source based on the experience of testers.The entire diagnosis process is complicated,technically difficult,and the diagnosis result shows lag.The accuracy of traditional electromagnetic compatibility fault diagnosis results relies largely on the level of the ability of testers,and the traditional technique lacks further mining and analysis of the test data.Therefore,faced with the same system electromagnetic compatibility fault,different testers may give different diagnoses.In order to improve the accuracy,timeliness as well as the operability of electromagnetic compatibility fault diagnosis,this thesis proposes an electromagnetic compatibility test data analysis and processing technique based on wavelet transform.This thesis is organized as follows.The first part studies the significance and background of electromagnetic compatibility test data analysis and processing technique,and introduces the main work of this article according to the current development status at home and abroad.The second part mainly studies the acquisition standard of electromagnetic compatibility test data,and has an in-depth understanding of the standard test items and test methods of electromagnetic compatibility.It analyzes the shortcomings of traditional electromagnetic compatibility fault diagnosis technology,and puts forward the specific research direction and technical route of electromagnetic compatibility test data analysis and processing technology according to the actual needs of electromagnetic compatibility fault diagnosis technology based on pattern recognition ideas.The third part focuses on the application of wavelet transform theory in the analysis and processing of electromagnetic compatibility test data.First of all,the noise of the test data is eliminated through wavelet denoising technology.And then the energy characteristic parameters of electromagnetic compatibility test data will be extracted combined with wavelet packet theory.Finally,the peak feature and envelope feature extraction scheme will be studied according to the needs of electromagnetic compatibility test data analysis and processing.The fourth part focuses on the application of BP neural network in electromagnetic compatibility analysis and processing technology.Based on the feature extraction results of the third part,a feature sample library will be built in the beginning.And then use BP neural network algorithm to train it.Finally,this construction method will be verified.According to the examples given in this thesis,the diagnosis effect of BP neural network on different types of faults has an average recognition accuracy rate over 93%.The fifth part mainly uses MATLAB GUI to build an electromagnetic compatibility test data analysis and processing system that can be used by ordinary users.This system can realize the extraction of feature parameter extraction of test data,training of the neural network,diagnosis of fault and so on.