Online prediction method for remaining life of electromechanical equipment under situation of two-stage degradation

Abstract

The invention discloses an online prediction method for the remaining life of electromechanical equipment under the situation of two-stage degradation. The online prediction method can be applied to online service life prediction and health management of mechanical equipment and electric and electronic devices. The method comprises the steps that a Wiener process model serves as a basic degradation model of an object, and a degradation drifting coefficient is expanded into a state and described with a closed oblique Wiener process. A new algorithm is proposed to overcome prediction deviation caused by the Markovian feature of a common Wiener process. For state estimation in the online prediction stage, an iteration filter algorithm is proposed to obtain an analytical expression of updated states. On parameter estimation, a two-stage parameter estimation algorithm is proposed. An analytical expression related to remaining life prediction results is obtained by using updated states and parameters. The model proposed in the method better conforms to the general degradation rules, more accurate online remaining life prediction results can be obtained, and great significance is achieved on fault prediction and health management in engineering.

Description

technical field [0001] The invention belongs to the technical field of reliability engineering and relates to an online prediction method for the remaining life of electromechanical equipment under the condition of two-stage degradation. Background technique [0002] Prognostics and Health Management (PHM) is critical to the reliability and safety of running products and has been applied to many different products. The core of realizing fault prediction and health management lies in the prediction of equipment remaining life. Due to its good mathematical properties and physical interpretability, the Wiener process model is widely used in life data analysis in different industrial fields, such as LEDs in contact with image scanners, self-temperature heating cables, aluminum electrolytic cells, bridges and bearings . Further, in order to consider historical degradation data and current measurements, the adaptive Wiener process model has become a widely adopted predictive mod...

AI Technical Summary

Problems solved by technology

However, for the widely existing remaining life prediction of electromechanical equipment with two stages of slow degradation and accelerated degradation, the assumptions of the existing prediction methods based on the Wiener process are somewhat irrational, so more accurate prediction results cannot be obtained

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