Analog circuit early fault feature extraction method based on underdetermined blind source separation

Abstract

The invention discloses an analog circuit early fault feature extraction method based on underdetermined blind source separation. The method comprises the following concrete steps that (1) different test nodes are selected for different test circuits and the corresponding test excitation is inputted, and the circuit test point signals are acquired to form an observation signal matrix X(t); (2) theobservation signals X(t) of the time domain are converted into time-frequency domain signals by using short-time Fourier transform; (3) a hybrid matrix A is estimated through the fuzzy C-means clustering algorithm in the time-frequency domain; (4) the estimation values of the source signals in the time-frequency domain are obtained by using the hybrid matrix A obtained in the step three throughthe weighted minimum L1 norm method and then transformed to the time domain so as to obtain the recovered source signals S(t); and (5) the kurtosis of each source signal is calculated for the source signals S(t) obtained in the step four so as to form the feature vectors. The analog circuit early fault features can be effectively and accurately extracted so that the identifiability of the early fault features can be enhanced and the method plays an important role in later circuit fault diagnosis.

Description

Technical field [0001] The present invention relates to an early fault feature extraction technology of an analog circuit, in particular to an early fault feature extraction method of an analog circuit based on underdetermined blind source separation. Background technique [0002] With the development of science and technology, the structure and function of electronic systems are becoming increasingly complex, and the difficulty of circuit testing and diagnosis continues to increase. Relevant statistics show that the current proportion of digital-analog hybrid circuits in electronic equipment has exceeded 60%, and the probability of failure of less than 20% of analog circuits is as high as 80%, far exceeding the probability of failure of digital circuits. In recent years, with the rapid development of integrated circuit technology, the cost of circuit production and diagnosis has continued to rise. In the digital-analog hybrid integrated circuit, the analog circuit part only acc...

AI Technical Summary

Problems solved by technology

Relevant statistics show that the proportion of digital-analog hybrid circuits in electronic equipment has exceeded 60%, and the probability of failure of less than 20% of analog circuits is as high as 80%, far exceeding the probability of failure of digital circuits.

Most blind source separation methods require that the number of observed signals is not less than the number of source signals, but this condition is difficult to meet in the actual early fault diagnosis of analog circuits

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