Switching current circuit fault diagnosis method based on wavelet fractal and kernel principal characteristics

Abstract

The invention discloses a switching current circuit fault diagnosis method based on wavelet fractal and kernel principal characteristics. The method comprises the training step of a switching current circuit fault diagnosis module and the step of adopting the switching current circuit fault diagnosis module to carry out real-time fault diagnosis on a switching current circuit with faults. Wavelet decomposition and fractal analysis are combined to carry out characteristic extraction on fault signals, then kernel principal analysis is adopted to carry out optimal characteristic extraction on characteristic signals after wavelet fractal analysis, the faults of the switching current circuit are diagnosed through a support vector machine classifier, and when fault diagnosis is carried out on large-scale switching current circuit fault diagnosis and fault category overlapping, the characteristics of a proper number can be selected for the support vector machine to carry out fault diagnosis according to the complexity degree of fault data and the overlapping degree of fault categories, the fault classification rate is high, fault diagnosis is accurate, and the good generalization performance is achieved.

Description

technical field [0001] The invention belongs to the field of fault diagnosis of circuits and systems, and relates to a fault diagnosis method for switching current circuits based on wavelet fractal and kernel principal component features. Background technique [0002] Switching current technology is an analog sampling data signal processing technology proposed in the late 1980s that completely adopts digital CMOS process technology. It uses MOS transistors to maintain their drain through the charge stored on the gate oxide capacitor when their gates are open. polar current. Switching current technology does not require linear capacitors and high-performance operational amplifiers. It has the advantages of low voltage, high speed, broadband, and small chip area. It has developed rapidly in recent years. At present, there are relatively few studies on switching current circuit testing and fault diagnosis, and the main topics are testing principles, testing procedures, BIST an...

AI Technical Summary

Problems solved by technology

However, the aforementioned methods all use a fault characteristic parameter, which is only suitable for fault diagnosis of small-scale switching current circuits.

The fault classification rate is low when the number of fault transistors and the number of fault categories in which faults occur simultaneously in the circuit are large

And when fault classes overlap, there is no better solution

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