Fractional-order neural network performance degradation model and life prediction method for electronic products

Abstract

The invention discloses a fractional order neural network performance degradation model and a service life prediction method for an electronic product. The service life prediction method comprises the following concrete steps of: (1) performing a constant-stress accelerated life test on the electronic product to be tested, and acquiring performance degradation data under different stress levels; (2) calculating to obtain performance degradation data under stress T0 to be predicted by using the performance degradation data obtained in the (1) step and utilizing a GM (1,1) in a grey theory; (3) training a fractional order neural network by utilizing the performance degradation data, which are obtained in the (2) step, under the stress T0; (4) performing multistep prediction by utilizing the trained fractional order neural network in the (3) step; and (5) comparing a prediction value in the (4) step with a failure threshold of the electronic product, predicting failure time and then determining the service life of the electronic product. The service life prediction method for the electronic product is applicable to building the performance degradation model under different stresses; a failure mechanism of the electronic product is not required to be considered; and the service life prediction method is easy to implement and high in prediction accuracy.

Description

technical field [0001] The invention relates to fault prediction and health management prediction technology of electronic products, in particular to a fractional order neural network performance degradation model and life prediction method of electronic products. Background technique [0002] Aircraft Failure Prediction and Health Management (PHM) technology, as a key technology to realize system condition-based maintenance and autonomous support, can significantly reduce maintenance, use and support costs, improve aircraft safety and availability, and improve the readiness rate and mission of military aircraft. Success rate. With the rapid development of "more electric" aircraft and "all electric" aircraft, the life and reliability of airborne electronic products will affect the normal operation of the entire equipment and even the system. Accurate prediction of the life of airborne electronic products can provide an important basis for the preparation of backup parts, st...

AI Technical Summary

Problems solved by technology

Due to the complexity of the electronic product itself, it is difficult to know its failure mechanism accurately. At present, the life prediction of electronic products is mainly based on the monitoring performance degradation data.

Images