Research On Fault Diagnosis Of Analog Circuits

Fault diagnosis of analog circuits is very important in the process of electronic system design, production, using and maintain. Because there is much trouble in analog circuits, fault diagnosis of analog circuits already have been the restriction of circuit research. The research on fault diagnosis of analog circuits is an urgent subject in the circuit research field.In order to develop fault diagnosis of analog circuits, increase the theory reserves of fault diagnosis of analog circuits, put the technology of fault diagnosis of analog circuits into use, this dissertation study theory and technology of fault diagnosis of analog circuits integrally. Theory and technology of fault diagnosis of analog circuits is summarized at home and abroad. This dissertation study every field of fault diagnosis of analog circuits including the collection and handling of fault samples, the selection of optimal test points, the method and algorithm of fault diagnosis of analog circuits. Several kinds of new method of system analysis and fault diagnosis are proposed. The major study and result of this dissertation are the following.1. Grey entropy relational algorithm which come from the combination of grey relational analysis and grey entropy analysis is proposed to analyze and diagnose analog circuits because there is the character of grey system in analog circuits. Grey entropy relational degree is used to quantify the relationship between undiagnosed circuits and fault states. With the smaller samples and test points, grey entropy relational algorithm can ensure the accuracy of fault diagnosis of analog circuits. Grey entropy relational algorithm is proposed to select the optimal test points of analog circuits. Grey entropy relational degree is used to quantify the relationship between test points and fault components, grey entropy relational algorithm can ensure the objectivity of selecting the optimal test points.2. A new method based on clustering algorithm and Mahalanobis distance algorithm is proposed to diagnose analog circuits. Fuzzy C-means (FCM) clustering algorithm and hierarchical clustering algorithm are used to analyze fault samples of analog circuits. After clustering analysis, fault samples are classified, fault dictionary is structured simultaneously. Mahalanobis distance algorithm and fault dictionary method are combined to finish fault diagnosis of analog circuits. This method can utilize the excellent classification ability of clustering algorithm and the excellent distance calculation ability of Mahal anobis distance algorithm. Traditional fault dictionary method is expanded. This method has the advantages of smooth process and practical applicability.3. Fuzzy membership function is transformed to quantify the fault degree of analog circuits. Several common fault degree quantification function are set up. Fault degree quantification algorithm based on fault degree quantification function and decision function is proposed to calculate the fault index of analog circuits. Fault index of analog circuits can evaluate the fault degree of analog circuits objectively, describe analog circuit system accurately. Fuzzy algorithm based on membership function and decision function is used to diagnose analog circuits accurately. The similarity between undiagnosed circuits fault states is quantified by Fuzzy algorithm.4. A new method based on reclassification and SVM is proposed to diagnose analog circuits. Two method of reclassification are studyed to reclassify fault samples of types overlap. The classification result of SVM prove that reclassification can increase the accuracy of fault diagnosis when there is overlap area in fault samples of different fault types.This dissertation consists of6chapters, including41figures,54tables and115references.