Reliability analysis based on the principle of maximum entropy and Dempster–Shafer evidence theory
| Autor: | Qiu Jiwei, Ma Yupeng, Zhang Jianguo |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Mechanical Engineering
Principle of maximum entropy Cumulative distribution function 020101 civil engineering Probability density function 02 engineering and technology Interval (mathematics) Standard deviation 0201 civil engineering 020303 mechanical engineering & transports 0203 mechanical engineering Mechanics of Materials Dempster–Shafer theory Applied mathematics Entropy (information theory) Reliability (statistics) Mathematics |
| Zdroj: | Journal of Mechanical Science and Technology. 32:605-613 |
| ISSN: | 1976-3824 1738-494X |
| DOI: | 10.1007/s12206-018-0107-3 |
| Popis: | The Probability density functions (PDFs) of some uncertain parameters are difficult to determine precisely due to insufficient information. Only the varying intervals of such parameters can be obtained. A method of reliability analysis based on the principle of maximum entropy and evidence theory was proposed to address the reliability problems of random and interval parameters. First, the PDFs and cumulative distribution functions of interval parameters were obtained on the basis of the principle of maximum entropy and Dempster–Shafer evidence theory. Second, the normalized means and standard deviations of interval parameters were obtained using the equivalent normalization method. Third, two explicit iteration algorithms of reliability analysis were proposed on the basis of the advanced firstorder and second-moment method to avoid solving the limit state function and obtain the reliability index. Finally, the accuracy and efficiency of the proposed methods were verified through a numerical example and an engineering case. |
| Databáze: | OpenAIRE |
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