The Research On Fault Propagation Characteristics Of Large-scale Analog Circuit

Analog circuit fault diagnosis is always the research focus in circuit and system field.However, available data for circuit diagnosis is limited in the large scale circuits especially with package design.Even if information process with various testing signal is adopted,it's very difficult to solve the problem of diagnosis information deficiency. The problem restricts the further development of analog circuit fault diagnosis. As we know, the fault signals propagating through the circuit are the important diagnosis information, but at the same time they can cause great arduousness and severe interference for the identification and location of true fault sources.Therefore,it is necessary to trace the fault signal and analyze the fault propagation characteristics.For this reason, this paper aims at the analysis method, simulation model and its application of fault propagation characteristics in analog circuits.At first, in view of the affinity between fault propagation characteristic and the circuit topology, this thesis verifies the small-world and scale-free feature of large-scale circuits with the case study of benchmark circuits for test,and discusses the method and implement for hierarchical division of large scale circuits.Meanwhile, under the consideration of the uncertainty of fault pattern division, cloud theory is introduced to implement the fault pattern division of circuits and the initial sample point spread. On this basis, a behavior modeling method based on data field for fault propagation is proposed. The proposed method can describe interaction of the fault patterns and fault propagation behavior.In order to analyze fault propagation characteristics of analog circuits, a Co-simulation and modeling method for fault propagation behavior is proposed with a case study to explain its procedure. The proposed method combines graph theory, fuzzy theory and probability theory with complex network. The internal mechanism of fault propagation such as small world and scale-free characteristics are found from the model parameters. The parameters such as node degree data, maximum probability propagation path, clustering coefficient, average path length and so on can be applied in fault diagnosis. Then, this paper focuses on the problems that wavelet multi-resolution analysis of the small-world feature and on the robustness and vulnerability analysis.Furthermore, this paper applies the proposed complex network model of fault propagation to searching fault propagation paths,faults location, and accessible nodes design.The case study indicates its accuracy and efficiency.