Reliability Analysis with Multiple Dependent Features from a Vibration-Based Accelerated Degradation Test
Accelerated degradation testing (ADT) has been widely used for reliability prediction of highly reliable products. In many applications, ADT data consists of multiple degradation-related features, and these features are usually dependent. When dealing with such ADT data, it is important to fully uti...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2016/2315916 |
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| _version_ | 1850223082252271616 |
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| author | Fuqiang Sun Jingcheng Liu Xiaoyang Li Haitao Liao |
| author_facet | Fuqiang Sun Jingcheng Liu Xiaoyang Li Haitao Liao |
| author_sort | Fuqiang Sun |
| collection | DOAJ |
| description | Accelerated degradation testing (ADT) has been widely used for reliability prediction of highly reliable products. In many applications, ADT data consists of multiple degradation-related features, and these features are usually dependent. When dealing with such ADT data, it is important to fully utilize the multiple degradation features and take into account their inherent dependency. This paper proposes a novel reliability-assessment method that combines Brownian motion and copulas to model ADT data obtained from vibration signals. In particular, degradation feature extraction is first carried out using the raw vibration signals, and a feature selection method quantifying feature properties, such as trendability, monotonicity, and robustness, is adopted to determine the most suitable degradation features. Then, a multivariate s-dependent ADT model is developed, where a Brownian motion is used to depict the degradation path of each degradation feature and a copula function is employed to describe the dependence among these degradation features. Finally, the proposed ADT model is demonstrated using the vibration-based ADT data for an electric motor. |
| format | Article |
| id | doaj-art-6b9cc7bbaa9c4d108d385fc4f6e6bc77 |
| institution | OA Journals |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-6b9cc7bbaa9c4d108d385fc4f6e6bc772025-08-20T02:06:06ZengWileyShock and Vibration1070-96221875-92032016-01-01201610.1155/2016/23159162315916Reliability Analysis with Multiple Dependent Features from a Vibration-Based Accelerated Degradation TestFuqiang Sun0Jingcheng Liu1Xiaoyang Li2Haitao Liao3Science and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaScience and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaScience and Technology on Reliability and Environmental Engineering Laboratory, School of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaDepartment of Industrial Engineering, University of Arkansas, Fayetteville, AR 72701, USAAccelerated degradation testing (ADT) has been widely used for reliability prediction of highly reliable products. In many applications, ADT data consists of multiple degradation-related features, and these features are usually dependent. When dealing with such ADT data, it is important to fully utilize the multiple degradation features and take into account their inherent dependency. This paper proposes a novel reliability-assessment method that combines Brownian motion and copulas to model ADT data obtained from vibration signals. In particular, degradation feature extraction is first carried out using the raw vibration signals, and a feature selection method quantifying feature properties, such as trendability, monotonicity, and robustness, is adopted to determine the most suitable degradation features. Then, a multivariate s-dependent ADT model is developed, where a Brownian motion is used to depict the degradation path of each degradation feature and a copula function is employed to describe the dependence among these degradation features. Finally, the proposed ADT model is demonstrated using the vibration-based ADT data for an electric motor.http://dx.doi.org/10.1155/2016/2315916 |
| spellingShingle | Fuqiang Sun Jingcheng Liu Xiaoyang Li Haitao Liao Reliability Analysis with Multiple Dependent Features from a Vibration-Based Accelerated Degradation Test Shock and Vibration |
| title | Reliability Analysis with Multiple Dependent Features from a Vibration-Based Accelerated Degradation Test |
| title_full | Reliability Analysis with Multiple Dependent Features from a Vibration-Based Accelerated Degradation Test |
| title_fullStr | Reliability Analysis with Multiple Dependent Features from a Vibration-Based Accelerated Degradation Test |
| title_full_unstemmed | Reliability Analysis with Multiple Dependent Features from a Vibration-Based Accelerated Degradation Test |
| title_short | Reliability Analysis with Multiple Dependent Features from a Vibration-Based Accelerated Degradation Test |
| title_sort | reliability analysis with multiple dependent features from a vibration based accelerated degradation test |
| url | http://dx.doi.org/10.1155/2016/2315916 |
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