Artificial circuit fault diagnosis method based on wavelet analysis and limited gauss mixed model expectation maximization (EM) method

Abstract

The invention relates to an artificial circuit fault diagnosis method. The method based on wavelet analysis and a limited gauss mixed model expectation maximization (EM) method conducts diagnosis on artificial circuit fault. The method introduces a 'sub-health' concept to describe the operating situation of a circuit system with 'a disease', and defines a sub-healthy state of a tolerance artificial circuit as a circuit component sub-health and a circuit system sub-health. Objective selection of wavelet basis is achieved by a volatility function, the wavelet analysis of sampled data is conducted, and diagnosis of an artificial circuit is conducted by combining and based on the limited gauss mixed model EM method. Each fault feature distribution situation can be well described by a gauss mixed model as diagnosis modeling, so that the problem of overlapped projection of a fault model is well solved. EM arithmetic is adopted to conduct failure classification and provide novel ideas for soft fault diagnosis of the simulated circuit.

Description

technical field [0001] The invention relates to an analog circuit fault diagnosis method based on wavelet analysis and finite Gaussian mixture model EM method, belonging to the technical field of analog circuit fault diagnosis. Background technique [0002] Since the end of the 1950s and the beginning of the 1960s, people have carried out a series of explorations on the automation of fault diagnosis. At present, the fault diagnosis of digital circuits has achieved relatively satisfactory results, and a large number of effective diagnosis and test generation methods have emerged. However, the research results of analog circuit fault diagnosis are not ideal. According to data reports, although digital circuits account for more than 80% of electronic equipment, more than 80% of equipment failures occur in analog circuits. Faults in analog circuits are distinguished according to their nature and can be divided into hard faults and soft faults. Hard faults, also known as large...

AI Technical Summary

Problems solved by technology

However, there is an intermediate transition state between normal and faulty circuits, how to define this intermediate state and how it affects the circuit, and how to accurately describe this effect, by consulting the literature, there is no reasonable method so far to be able to solve this problem

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