The Research Of Analog Circuit Fault Diagnosis Method Based On Genetic Wavelet Neural Network

With the quick development of information processing technology today, the circuit in electronic equipment become increasingly complex, thus to deal with equipment failure problems caused by analog circuits effective become increasingly difficult. As the integrated circuit getting higher and the inherent instability of component itself and other reasons,it is more challenges to locate faults and process faults quickly.Faced with numerous problems, the traditional fault diagnosis methods have been unable to meet the needs of social development and new diagnostic techniques demand is imminent.Researchers from different countries began to try new theory, which the neural network as an intelligent technology applied in analog circuit diagnosis research get fast development, and has opened up a new path in term of new diagnostic technologies, and obtained a number of achievements over a period of time.Nowadays, more and more scholars have begun to pay attention to the new technology that many theory based on wavelet analysis, genetic algorithm and fusion theory combined with neural network processing fault diagnosis,which provides a new way forintelligent fault diagnosis technology.Lab VIEW software as a powerful graphical programming software, can provide good human interaction interface, has been applied to fault diagnosis technology and provides a convenient way to achieve the facilitation of the fault diagnosis.Based on the new diagnostic technique,this paper integrate the wavelet analysis and the genetic algorithm theory into neural network, combined with virtual instruments(Lab VIEW platform), to achieve the visualized diagnosis of electrical faults. This paper introduces research background and significance of fault diagnosis of analog circuits;domestic and international development present situation;the existing problems and classification methods. Then overview of artificial neural networks theory, including its features, applications and learning styles. Based on BP- neural network theory,this paper construct the structure of wavelet neural network and introduces its improved algorithm in detail,and validate the correctness of the proposed algorihtm through the simulation example, including use the ORCAD10.5 software to extract the raw data in analog circuit diagnosis;using the MATLAB software platform programming for multi-resolution analysis of the data, extracting the fault characteristic valueand constructing the sample set; the achievement of the fault diagnosis based on wavelet neural network method. For the problem of neural network weights, by using the genetic algorithms to optimize and to improve network performance.Finally it realize graphical programming and builds the interface of analog circuit fault diagnosis system through Lab VIEW software platform, then diagnosis is visualization and simplification.