Analogue circuit fault diagnosis method based on improved type clone selection algorithm

Abstract

The invention discloses an analogue circuit fault diagnosis method based on an improved type clone selection algorithm. The method includes the first step of canceling the decision rules that an original decision algorithm determines which diagnosis radiuses faults belong to based on experience, and adopting the minimum Euclidean distance as a diagnosis decision condition, the second step of modifying an affinity calculation formula and utilizing a formula f=1/(1+d) to replace an original formula f=1/d so as to prevent overflowing in calculation and standardize the affinity within a fixed range of (0,1], and the third step of modifying an overall affinity calculation mode and utilizing an average value expression method of the affinity of all individuals in a species group to replace a sum expression method of the affinity of all the individuals in the species group. Through the first step, failure switch-off can be eliminated, false switch-off and excessive switch-off can be reduced and the fault diagnosis rate can be improved. Through the second step, calculation is convenient and the comparability of the affinity is higher. The improved type clone selection algorithm is applied to analogue circuit fault diagnosis and has superior performance.

Description

technical field [0001] The invention relates to the field of circuit fault diagnosis, in particular to the field of analog circuit fault diagnosis based on a clone selection algorithm. Background technique [0002] With the rapid development of electronic technology, circuit test diagnosis, especially analog circuit fault diagnosis is becoming more and more complicated. At present, the clone selection algorithm in the artificial immune technology is the most active branch in the field of fault diagnosis, and it is also one of the most prominent technologies in the artificial immune technology, which has the incomparable fast convergence ability of the neural network. At the same time, many variants of clone selection algorithms have appeared in recent years, some of which have been applied to analog circuit fault diagnosis and have shown their superior performance. [0003] The advantage of the clonal selection algorithm is that it uses high-frequency mutation and cloning a...

AI Technical Summary

Problems solved by technology

The disadvantage is that high-frequency mutation has uncertainty; the higher the affinity, the greater the number of clones, which will increase the size of the clone and the amount of calculation; the result may not be globally optimal, specifically the following disadvantages: the decision in the algorithm Setting a unified judgment radius in the condition will result in fault rejection and multiple points; and it is difficult to determine the size of the judgment radius; the calculation method of affinity is f=1 / d, and it will cause calculation overflow when d=0

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