Mechanical structure residual life prediction method based on Wiener process and P-EMD

Abstract

The invention provides a mechanical structure residual life prediction method based on a Wiener process and P-EMD, and belongs to the technical field of mechanical product residual life prediction. The method comprises the steps that a P-EMD is adopted to decompose a collected vibration signal of a mechanical structure to obtain a plurality of IMFs, the P-EMD represents empirical mode decomposition based on particle swarm optimization and Hermite interpolation polynomial, and the IMFs represent eigenmode functions; calculating the approximate entropy of the IMF signal obtained by decomposition, and judging the degradation trend of the approximate entropy; and based on the change trajectory of the approximate entropy, predicting the residual life of the mechanical structure by using a residual life prediction model based on a Wiener process. The method can improve the prediction precision of the residual life of the mechanical structure.

Description

technical field [0001] The invention relates to the technical field of remaining life prediction of mechanical products, in particular to a method for predicting the remaining life of a mechanical structure based on Wiener process and P-EMD. Background technique [0002] The estimation and evaluation of the remaining life of complex mechanical structural parts is very important for the safety and reliability of equipment. This technology has become a widely researched issue in high-speed rail, automobile, aerospace and other industries. [0003] Common equipment failures include improper installation, improper storage, improper lubrication, etc. Multiple failure mechanisms are coupled and superimposed, resulting in aliasing of equipment failure modes. When the structure of the equipment is complex, the working environment is changeable, and the failure modes are diverse, the commonly used remaining life estimation method based on mechanism modeling and analysis cannot give ...

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Problems solved by technology

[0003] Common equipment failures include improper installation, improper storage, improper lubrication, etc. Multiple failure mechanisms are coupled and superimposed, resulting in aliasing of equipment failure modes

When the structure of the equipment is complex, the working environment is changeable, and the failure modes are diverse, the commonly used remaining life estimation method based on mechanism modeling and analysis cannot give a comparative analysis due to the existence of model uncertainty and environmental uncertainty. good analysis result

[0004] The existing remaining life estimation methods can be roughly divided into three types, including experience-based, model-based, and data-driven methods; among them, the experience-based and model-based methods rely on a thorough analysis of the structural failure mechanism on the one hand, and often It is necessary to establish a high-precision simulation model for the structure, the workload is huge, the calculation is complicated, and it is difficult to simulate the degradation process of equipment performance before failure; Sufficient failure samples, even under test conditions, to obtain failure data

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