Electronic-complete-machine-storage-life assessment method and device

Abstract

The invention discloses an electronic-complete-machine-storage-life assessment method and device. The method includes the steps that performance degradation data and the natural storage time of an electronic complete machine are obtained; a degradation data trend model is established according to test samples in the performance degradation data, and the forecasted service life of the electronic complete machine is obtained according to the degradation data trend model and verification samples in the performance degradation data; accelerated factors are obtained according to the natural storage time and a pre-established accelerating model; the characteristic service life of the electronic complete machine is obtained according to the forecasted service life of the electronic complete machine and the accelerated factors. According to the electronic-complete-machine-storage-life assessment method and device, the performance degradation data of the electronic complete machine is analyzed, the service life of the electronic complete machine is assessed according to the analyzed result, the accelerated factors of the electronic complete machine are analyzed based on storage time of the electronic complete machine, the characteristic service life of the electronic complete machine is further assessed in cooperation with the assessed service life and the accelerated factors, and the electronic-complete-machine-storage-life assessment method and device have the advantage of being high in assessment accuracy.

Description

technical field [0001] The invention relates to the technical field of electronic complete sets, in particular to a storage life evaluation method and device for electronic complete sets. Background technique [0002] In the accelerated storage test of electronic complete equipment, due to the complex functions of electronic complete equipment and other reasons, there are situations in which product performance degradation rules are complex, and natural storage data and accelerated storage test data coexist. This situation makes it difficult to evaluate the test results. The traditional accelerated test data evaluation method cannot deal with the data in this situation, making it impossible to evaluate the acceleration factor or storage life of the product, and the purpose of the test cannot be achieved. [0003] The evaluation method for the complex performance degradation law of electronic complete products and the coexistence of natural storage data and accelerated storag...

AI Technical Summary

Problems solved by technology

[0004] When predicting the trend of product performance degradation, the commonly used processing method is the regression analysis method. The regression analysis method uses linear functions, exponential functions, power functions, etc. to perform regression fitting on the performance degradation data of the product to obtain the regression equation of the degradation trend. Then predict the degradation trend, but for some nonlinear degradation data with complex rules, the accuracy of the regression analysis method is not high, and sometimes it is difficult to apply

At present, the hot spot of research is artificial neural network method, but in engineering application, artificial neural network method is not ideal for the prediction of product degradation trend, and its application needs further research

[0005] In the process of realizing the present invention, the inventors found that for the coexistence of natural storage data and accelerated storage test data, the current processing method is to first use the accelerated test data to evaluate the test results to obtain the storage life of the product, and then simply in the Adding the natural storage time to the life expectancy results, and sometimes even ignoring the natural storage data when evaluating the acceleration factor, these processing methods will make the evaluation results biased

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