Chen, Rentong and Zhang, Chao and Wang, Shaoping and Hong, Li (2022) Bivariate-Dependent Reliability Estimation Model Based on Inverse Gaussian Processes and Copulas Fusing Multisource Information. Aerospace, 9 (7). p. 392. ISSN 2226-4310
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Abstract
Reliability estimation for key components of a mechanical system is of great importance in prognosis and health management in aviation industry. Both degradation data and failure time data contain abundant reliability information from different sources. Considering multiple variable-dependent degradation performance indicators for mechanical components is also an effective approach to improve the accuracy of reliability estimation. This study develops a bivariate-dependent reliability estimation model based on inverse Gaussian process and copulas fusing degradation data and failure time data within one computation framework. The inverse Gaussian process model is used to describe the degradation process of each performance indicator. Copula functions are used to capture the dependent relationship between the two performance indicators. In order to improve the reliability estimation accuracy, both degradation data and failure time data are used simultaneously to estimate the unknown parameters in the degradation model based on the likelihood function transformed using the zeros-ones trick. A simulation study and a real application in the reliability estimation of mechanical seal used in airborne hydraulic pump are conducted to validate the effectiveness and accuracy of the proposed model compared with existing reliability models.
Item Type: | Article |
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Subjects: | OA Open Library > Engineering |
Depositing User: | Unnamed user with email support@oaopenlibrary.com |
Date Deposited: | 07 Apr 2023 08:05 |
Last Modified: | 07 Feb 2024 04:28 |
URI: | http://archive.sdpublishers.com/id/eprint/472 |