Fault prediction method of aviation power converter based on fractional order UPF

Abstract

The invention discloses an aviation power converter failure prediction method based on factional order UPE. According to the method, firstly, state signals of measurement points of an aviation power converter are collected in real time, failure characteristic parameters reflecting the performance degradation condition of the aviation power converter are extracted, and history time sequence values of the failure characteristic parameters are obtained; then, a state equation of the performance degradation process of the aviation power converter is trained on the basis of an LS-SVM model, and a fractional order state space model of the performance degradation process of the aviation power converter is built; ultimately, by combination of the fractional order state space model, time sequence prediction is carried out on the failure characteristic parameters by means of the fractional order UPE, and failure prediction of the aviation power converter is achieved. The invention provides the aviation power converter failure prediction method based on an improved PF algorithm, proposal distribution of particles is generated by means of the fractional order UKF algorithm, a particle degradation problem of a traditional PF algorithm is solved, the performance degradation process of the converter is described by means of the fractional order state space model so as to accord with practical situations, and failure prediction precision of the aviation power converter is improved.

Description

technical field [0001] The invention relates to a fault prediction method for an aviation power converter based on a fractional UPF, and belongs to the field of circuit test evaluation and fault prediction. Background technique [0002] With the continuous improvement of the advanced nature of modern aircraft and the rapid development of multi-electric aircraft, the number of avionics equipment is increasing day by day, and the power consumption of avionics equipment has increased significantly, which has raised the importance of avionics power supply to a new level. requirements are also getting higher. Aviation power supply includes main power supply, secondary power supply, auxiliary power supply and so on. Aviation power converters include secondary power supplies and working power supplies for various avionics equipment, and are an essential part of aviation power systems. Therefore, the study of aviation power converter fault prediction technology has important engin...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the nonlinearity and time-varying nature of the performance degradation law of the aviation power converter and the noise interference in the prediction process, the present invention proposes a fault prediction method for the aviation power converter based on the fractional-order unscented particle filter (Unscented Particle Filter, UPF)

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