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| Minimum Variation-Maximum Likelihood Estimation of Three-parameter Weibull Distribution under Accelerated Life Test |
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| DOI：10.7643/issn.1672-9242.2023.05.003 |
| KeyWord:three-parameter Weibull distribution coefficient of variation accelerated life test mechanism equivalence reliability evaluation lifetime prediction |
| Author | Institution |
| MA Xiao-bing |
School of Reliability and Systems Engineering, Beihang University, Beijing , China |
| LIU Yu-jie |
School of Reliability and Systems Engineering, Beihang University, Beijing , China |
| WANG Han |
School of Reliability and Systems Engineering, Beihang University, Beijing , China |
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| Abstract: |
| The work aims to estimate the reliability and predict the lifetime of the products subject to three-parameter Weibull distribution under accelerated life test, so as to solve the problem that the traditional methods are difficult to complete the calculation when the shape parameter is less than 1. Through the conversion relationship between three-parameter Weibull distribution and exponential distribution, the best estimated value of the location parameter was determined with the error of coefficient of variation as the optimization objective. Then, the analogue maximum likelihood method was used to estimate the remaining parameters of the Weibull distribution, based on which the minimum variation-maximum likelihood estimation (MV-MLE) was constructed. According to the principle of constant failure mechanism in accelerated life test, the proposed method was extended to evaluate the reliable lifetime of products under multiple stress levels while ensuring the failure mechanism equivalence. The effectiveness of the proposed method was verified by simulations under both single stress level and multiple stress levels. Compared with traditional methods, the proposed method improved the estimation accuracy of shape parameter (i.e. mechanism equivalence parameter) by more than 40% with small samples. The proposed method performs high accuracy for parameter estimation and lifetime prediction of three-parameter Weibull distribution, which overcomes the defects of traditional methods, and has good application effects in the evaluation of accelerated life test. |
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