Analog circuit fault diagnosis method based on improvement

Abstract

The invention provides an analog circuit fault diagnosis method based on improvement. The conventional technology is improved from two aspects: 1. a DAGSVA method is improved: an SVM with the maximum inter-class distance acts as the uppermost layer node of the DAGSVM. If the root node classification result is i-type, the SVM with the maximum inter-class distance to the i-type is selected to act as the child node of the layer, and if the root node classification result is j-type, the SVM with the maximum inter-class distance to the j-type is selected to act as the child node of the layer; if the classification result does not belong to the i-type or the j-type, the two types are eliminated, two types of SVM with the maximum inter-class distance Dij are selected among the rest classes to act as the nodes of the layer, and the two aforementioned steps are continued unit a diagnosis result is obtained so that a situation of error of the final result caused by high-layer node diagnosis error can be effectively avoided. 2. particle swarm optimization (PSO) is performed on each child SVM for parameter optimization in order to enhance diagnosis accuracy rate of each child node so that SVM diagnosis accuracy rate of each node is enhanced, and thus diagnosis accuracy rate of the whole DAGSVM is enhanced.

Description

technical field [0001] The invention relates to the field of analog circuit fault diagnosis, in particular to an improved analog circuit fault diagnosis method. Background technique [0002] With the continuous development of electronic technology and computer technology, the structure of equipment is becoming more and more complex. However, the analog circuit in the equipment is often prone to problems, resulting in high test time and test cost. With the development trend of circuit structures expanding and becoming more and more complex, the difficulty of testing has also become higher. The scale and complexity of modern circuit systems are getting larger and higher, and the requirements for reliability and fault diagnosis of circuit systems are also increasing. Theoretical analysis and practical application show that analog circuits are more prone to failure than digital circuits. Although digital circuits in electronic equipment exceed 80%, more than 80% of the failure...

AI Technical Summary

Problems solved by technology

The DAGSVM algorithm also has certain problems: when the classification result of the previous node is wrong, the classification result of the subsequent node is also wrong, so that the correct result cannot be obtained.

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