Analog circuit fault prediction method based on ARMA (Autoregressive Moving Average)

Abstract

The invention discloses an analog circuit fault prediction method based on ARMA (Autoregressive Moving Average), which comprises the following steps: extracting a plurality of characteristic quantities of a plurality of measuring points of an analog circuit to form a characteristic vector which can characterize fault information; utilizing an ARMA model to predict the characteristic vector to obtain a predicted characteristic vector; using the weighting Mahalanobis distance to calculate the distance between the obtained characteristic vector and a characteristic vector set in a circuit fault-free tolerance range; comparing the calculated distance and the maximum value of the Mahalanobis distance in the fault-free tolerance range, and converting the deviation degree of the calculated distance and the maximum value of the Mahalanobis distance to a fault occurring rate; and more intuitively monitoring the healthy state of the analog circuit. By experiment verification, the method can be used for better predicting the health state of the analog circuit, has a high fault detection rate, and can be used for the early monitoring of the analog circuit fault well.

Description

technical field [0001] The invention belongs to the technical field of electrical signal processing, and more specifically relates to an analog circuit fault prediction method based on autoregressive moving average. Background technique [0002] At present, analog circuits have been widely used in various aspects such as automatic control, measuring instruments, military industry, etc., and with the development of electronic technology, the electronic systems composed of analog circuits are becoming more and more complex, and subsequent maintenance and regular maintenance will inevitably pay high maintenance costs fee, no longer applicable. Therefore, it is very necessary to predict the failure of the analog circuit, so as to perform condition-based maintenance. [0003] At present, there are many researches on analog circuit fault prediction methods at home and abroad. Among them, the autoregressive moving average (ARMA) model is a classic method for system identification ...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to overcome the defect that the numerical value predicted by the ARMA prediction model alone cannot be intuitively related to the health state of the analog circuit in the prior art, and provides a method for predicting faults of analog circuits based on autoregressive moving average to more intuitively Monitor the health status of analog circuits, good for early detection of analog circuit failures

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