Method of Health Monitoring and Fault Prediction of DC-DC Converter Based on Multiple SVDD Models

Abstract

The invention discloses a DC-DC converter health monitoring and fault prediction method based on multiple SVDD models. Firstly, a state signal (input voltage, input current, output voltage and output current) of a health DC-DC converter is acquired, and multi-group performance parameters (an output voltage average value Uo, an output ripple voltage Upp and efficiency Eta) are calculated; then three training sample sets are constructed, and three SVDD models of a circuit under the health state are acquired; after a health reference value of the circuit is calculated, the DC-DC converter to be tested is monitored, relative distance of all the performance parameters (Uo, Upp and Eta) to the corresponding SVDD models is calculated and summation is performed in a weighting way so that a circuit fault characteristic parameter Hk is acquired; and the Hk is compared with the reference value, and when Hk is less than the reference value, the circuit is in the abnormal state, and thus fault prediction is performed on the circuit by adopting a Gauss process model. Variation situations of the multiple performance parameters of the DC-DC converter are comprehensively considered so that defects of single information are compensated, the fault characteristic parameter capable of comprehensively assessing the performance state of the circuit is acquired and accurate fault prediction of the circuit can be effectively realized.

Description

technical field [0001] The invention relates to a DC-DC converter health monitoring and fault prediction method based on multiple SVDD models, belonging to the field of reliability evaluation and fault prediction. Background technique [0002] With the increasing number of aircraft electrical equipment, the power consumption of airborne electronic equipment has increased significantly, which puts forward higher requirements for the power supply quality of the aircraft power system. As an important part of the aircraft power system, the DC-DC converter provides DC power for various airborne electronic devices. The DC-DC converter has been operating in a harsh environment at high altitude for a long time, and its potential for failure is relatively high. Once a failure occurs, it will cause major losses to the entire aircraft power system. Therefore, it is necessary to conduct fault prediction technology research on DC / DC converters in order to predict the occurrence of fault...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem that most of the fault characteristic parameters of the current DC-DC converter are single information parameters, which cannot comprehensively and accurately reflect the degradation of circuit performance, the present invention proposes a DC-DC based on a multi-Support Vector Data Description (SVDD) model Converter fault characteristic parameter extraction method, and use it in health monitoring and fault prediction

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