A Nonlinear Prognostic Model Based on the Wiener Process with Three Sources of Uncertainty
Estimation of the remaining useful life (RUL) is an important component of prognostics and health management (PHM). The accuracy of the RUL estimation for complex systems is mainly affected by three sources of uncertainty, i.e., the temporal uncertainty, the product-to-product uncertainty, and measu...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2021/6475056 |
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| author | Huifang Niu Jianchao Zeng Hui Shi Bin Wang Tianye Liu |
| author_facet | Huifang Niu Jianchao Zeng Hui Shi Bin Wang Tianye Liu |
| author_sort | Huifang Niu |
| collection | DOAJ |
| description | Estimation of the remaining useful life (RUL) is an important component of prognostics and health management (PHM). The accuracy of the RUL estimation for complex systems is mainly affected by three sources of uncertainty, i.e., the temporal uncertainty, the product-to-product uncertainty, and measurement errors. To improve PHM and account for the effects of the three sources of uncertainty, a nonlinear prognostic model with three sources of uncertainty is presented here. An approximated analytical expression for the probability density function (PDF) of the RUL is obtained based on the concept of first hitting time (FHT). Model parameters are then obtained by the expectation maximization (EM) algorithm, and the drift parameter is estimated adaptively using a Bayesian procedure. Finally, in order to illustrate the practical applications of the presented approach, a comparative study of real data on fatigue crack propagation is presented. Results demonstrate that our method improves model fit and increases the accuracy of the lifetime estimation. |
| format | Article |
| id | doaj-art-2afd25f0d38e4fe19bc2e96273c51ae4 |
| institution | Kabale University |
| issn | 1875-9203 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-2afd25f0d38e4fe19bc2e96273c51ae42025-02-03T01:04:11ZengWileyShock and Vibration1875-92032021-01-01202110.1155/2021/6475056A Nonlinear Prognostic Model Based on the Wiener Process with Three Sources of UncertaintyHuifang Niu0Jianchao Zeng1Hui Shi2Bin Wang3Tianye Liu4Department of Data Science and TechnologyDepartment of Data Science and TechnologySchool of Electronic Information EngineeringDepartment of Data Science and TechnologyDepartment of Data Science and TechnologyEstimation of the remaining useful life (RUL) is an important component of prognostics and health management (PHM). The accuracy of the RUL estimation for complex systems is mainly affected by three sources of uncertainty, i.e., the temporal uncertainty, the product-to-product uncertainty, and measurement errors. To improve PHM and account for the effects of the three sources of uncertainty, a nonlinear prognostic model with three sources of uncertainty is presented here. An approximated analytical expression for the probability density function (PDF) of the RUL is obtained based on the concept of first hitting time (FHT). Model parameters are then obtained by the expectation maximization (EM) algorithm, and the drift parameter is estimated adaptively using a Bayesian procedure. Finally, in order to illustrate the practical applications of the presented approach, a comparative study of real data on fatigue crack propagation is presented. Results demonstrate that our method improves model fit and increases the accuracy of the lifetime estimation.http://dx.doi.org/10.1155/2021/6475056 |
| spellingShingle | Huifang Niu Jianchao Zeng Hui Shi Bin Wang Tianye Liu A Nonlinear Prognostic Model Based on the Wiener Process with Three Sources of Uncertainty Shock and Vibration |
| title | A Nonlinear Prognostic Model Based on the Wiener Process with Three Sources of Uncertainty |
| title_full | A Nonlinear Prognostic Model Based on the Wiener Process with Three Sources of Uncertainty |
| title_fullStr | A Nonlinear Prognostic Model Based on the Wiener Process with Three Sources of Uncertainty |
| title_full_unstemmed | A Nonlinear Prognostic Model Based on the Wiener Process with Three Sources of Uncertainty |
| title_short | A Nonlinear Prognostic Model Based on the Wiener Process with Three Sources of Uncertainty |
| title_sort | nonlinear prognostic model based on the wiener process with three sources of uncertainty |
| url | http://dx.doi.org/10.1155/2021/6475056 |
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