Interval prediction method of product performance degradation based on support vector machine and fuzzy information granulation

Abstract

The invention discloses a product performance degradation interval prediction method based on support vector machine (SVM) and fuzzy information granulation, comprising the following steps of: step 1, collecting product multi-parameter performance degradation data; step 2, analyzing principal components of the multi-parameter degradation data; step 3, executing fuzzy information granulation on the obtained principal component data; step 4, executing SVM modeling for the granulated data; step 5, executing interval prediction on product performance degradation trends. In the method, a fuzzy information granulation method and a SVM method are combined, the interval prediction method for the product performance degradation trends is presented for the first time, and the problem of prediction on the degradation trends of performance state and the changing space in the product running process is solved. The method solves the problem of evaluation and prediction under a condition that a plurality of output performance characteristic parameters of some products with complex structures concurrently degrade, based on the principal component analysis method.

Description

technical field [0001] The invention relates to an interval prediction method of product performance degradation trend based on a support vector machine and fuzzy information granulation, and belongs to the technical field of life prediction. Background technique [0002] With the advancement of science and technology and the development of industrial needs, all kinds of advanced products continue to develop in the direction of complexity, high speed, high efficiency, miniature or large scale, but on the other hand, they face more demanding working and operating environments. Once a key component of a product fails, it may affect the entire production process and cause huge economic losses. Therefore, how to evaluate the operating status of the product, so as to make a reasonable maintenance plan, ensure that the equipment is in a normal and stable working condition, and prevent catastrophic accidents are the most concerned and valued issues in various industries today. [...

AI Technical Summary

Problems solved by technology

In many cases, multiple performance parameters of the same product are physically related, but the results of mathematical calculations may be independent. This method does not take this into account

In addition, the joint probability density function in this method is determined by assumption, which may be quite different from the actual situation

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