Adaptive prediction method for residual life of equipment based on proportional accelerated degradation modeling

Abstract

The invention discloses an adaptive prediction method for the residual life of equipment based on proportional accelerated degradation modeling and relates to the technical field of equipment residual life prediction. Aiming at the residual life prediction problem of single equipment under an accelerated degradation test condition, firstly, a proportional accelerated degradation model is constructed based on a nonlinear Wiener process; secondly, a state transition equation is established on the basis of the degradation model, and the degradation state of the equipment is updated by adopting a Kalman filtering (KF) algorithm; thirdly, observation data of the performance degradation amount of the equipment is input, and an expectation maximization-Kalman filtering (EM-KF) algorithm is adopted to realize adaptive estimation of unknown parameters in the degradation model; and finally, on the basis of the updating of the degradation state and the adaptive estimation of the unknown parameters, a probability density function and a cumulative distribution function of the residual life of the equipment are calculated based on a total probability formula. By means of the method of the invention, more accurate residual life prediction under the accelerated degradation test of the single equipment is realized.

Description

technical field [0001] The invention relates to the technical field of equipment remaining life prediction, in particular to an adaptive prediction method for equipment remaining life based on proportional accelerated degradation modeling. Background technique [0002] In order to ensure flight safety and mission completion, airborne equipment generally has the characteristics of high reliability and long life, which makes it difficult for traditional life tests and degradation tests to quickly obtain sufficient life / degradation data to ensure the accuracy and accuracy of remaining life predictions. Scientificity of maintenance decision-making. In view of the deficiencies of traditional life / degradation test methods, accelerated degradation tests have gradually emerged and become an efficient and economical means of obtaining equipment degradation information. [0003] Affected by the environment and its own factors, the degradation process of equipment presents significant...

AI Technical Summary

Problems solved by technology

This method of remaining life prediction based on the status monitoring data from the initial operation to the current moment of a single equipment is also called the adaptive remaining life prediction method. At present, there are relatively few studies in this area, and it cannot be applied to accelerated stress occasions.

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