A Degraded Reliability Analysis Method Considering Measurement Error

Abstract

The invention discloses a measuring error-considering degradation reliability analysis method. The method is realized through the following steps: 1, selecting proper degradation parameters, recording a performance degradation value of each test piece at each test moment so that a performance parameter degradation amount can be converted to accord with a linear independent increment process rule through simple function transformation (such as logarithm transformation, index transformation and the like); 2, establishing a measuring error-considering linear independent increment process model; 3, calculating a likelihood function, and calculating unknown parameters in a degradation model through a maximum likelihood estimation method; and 4, carrying out reliability evaluation on a product by utilizing the established degradation model. The measuring error-considering degradation reliability analysis method has the advantages of being more suitable for the practical conditions of projects through considering the influences of measuring errors in degradation reliability modeling, and providing a feasible method for the maximum likelihood estimation of multidimensional variables with correlation by adopting a multidimensional theory of random processes to carry out analysis in the maximum likelihood estimation of model parameters.

Description

technical field [0001] Based on small sample reliability and non-stationary random process theory, this method establishes a degradation process model that considers measurement errors and can describe time-varying trends and time-varying dispersion, and models the reliability of degraded failure products in engineering analyze. It aims to improve the accuracy of performance degradation reliability analysis and evaluation, and belongs to the field of reliability engineering. Background technique [0002] In engineering practice, degraded failure refers to the phenomenon that the performance characteristics of products gradually deteriorate with the passage of time until they cannot meet the specified working conditions, such as the aging of materials, the wear and tear of mechanical parts, and so on. In engineering practice, most failure processes can be described by degeneration failure, so it is of great significance to model and analyze the degeneration failure process. ...

AI Technical Summary

Problems solved by technology

[0003] Although a large number of degradation phenomena have already appeared in engineering practice, the relevant theories and methods of reliability research based on degradation data are not yet perfect.

For example, the degradation process of many products is a non-stationary random process, and it is difficult to deal with it effectively with the more commonly used random process

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