A Robust Performance Degradation Modeling Approach Based on Student’s t-HMM and Nuisance Attribute Projection
Performance degradation assessment (PDA) is of great significance to ensure safety and availability of mechanical equipment. As an important issue of PDA, the robustness of the trained model directly affects the assessment efficiency and restricts its application in practice. This paper proposes a r...
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9032137/ |
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doaj-27a8381d095549bf88851ccd7132b0552021-03-30T01:28:42ZengIEEEIEEE Access2169-35362020-01-018496294964410.1109/ACCESS.2020.29800199032137A Robust Performance Degradation Modeling Approach Based on Student’s t-HMM and Nuisance Attribute ProjectionHuiming Jiang0https://orcid.org/0000-0003-1633-0429Jing Yuan1https://orcid.org/0000-0002-6978-7142Qian Zhao2https://orcid.org/0000-0003-2150-6257Han Yan3https://orcid.org/0000-0001-9336-6228Sen Wang4Yunfei Shao5https://orcid.org/0000-0003-2635-8150School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, ChinaSchool of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, ChinaSchool of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, ChinaSchool of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, ChinaShanghai Aerospace Control Technology Institute, Shanghai, ChinaSchool of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, ChinaPerformance degradation assessment (PDA) is of great significance to ensure safety and availability of mechanical equipment. As an important issue of PDA, the robustness of the trained model directly affects the assessment efficiency and restricts its application in practice. This paper proposes a robust modeling approach based on Student's t-hidden Markov model (Student's t-HMM) and nuisance attribute projection (NAP). NAP can remove nuisance attributes caused by individual differences from the feature space. Student's t-HMM utilizes the finite Student's t-mixture models (SMMs) to describe the observation emission densities associated with each hidden state, which can be more tolerant towards outliers than conventional HMMs. Based on these two techniques, the proposed method is supposed to be more robust and can assess the performance degradation process of new objects based on data of tested objects. The superiority of the proposed approach is evaluated using the vibration data from the accelerated life tests of bearings and the public XJTU-SY Bearing Datasets. The results demonstrate the robustness and effectiveness of the proposed approach for PDA modeling of rolling element bearings.https://ieeexplore.ieee.org/document/9032137/Robustnessperformance degradation assessmentstudent???s t-HMMnuisance attribute projectionbearings |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Huiming Jiang Jing Yuan Qian Zhao Han Yan Sen Wang Yunfei Shao |
| spellingShingle |
Huiming Jiang Jing Yuan Qian Zhao Han Yan Sen Wang Yunfei Shao A Robust Performance Degradation Modeling Approach Based on Student’s t-HMM and Nuisance Attribute Projection IEEE Access Robustness performance degradation assessment student???s t-HMM nuisance attribute projection bearings |
| author_facet |
Huiming Jiang Jing Yuan Qian Zhao Han Yan Sen Wang Yunfei Shao |
| author_sort |
Huiming Jiang |
| title |
A Robust Performance Degradation Modeling Approach Based on Student’s t-HMM and Nuisance Attribute Projection |
| title_short |
A Robust Performance Degradation Modeling Approach Based on Student’s t-HMM and Nuisance Attribute Projection |
| title_full |
A Robust Performance Degradation Modeling Approach Based on Student’s t-HMM and Nuisance Attribute Projection |
| title_fullStr |
A Robust Performance Degradation Modeling Approach Based on Student’s t-HMM and Nuisance Attribute Projection |
| title_full_unstemmed |
A Robust Performance Degradation Modeling Approach Based on Student’s t-HMM and Nuisance Attribute Projection |
| title_sort |
robust performance degradation modeling approach based on student’s t-hmm and nuisance attribute projection |
| publisher |
IEEE |
| series |
IEEE Access |
| issn |
2169-3536 |
| publishDate |
2020-01-01 |
| description |
Performance degradation assessment (PDA) is of great significance to ensure safety and availability of mechanical equipment. As an important issue of PDA, the robustness of the trained model directly affects the assessment efficiency and restricts its application in practice. This paper proposes a robust modeling approach based on Student's t-hidden Markov model (Student's t-HMM) and nuisance attribute projection (NAP). NAP can remove nuisance attributes caused by individual differences from the feature space. Student's t-HMM utilizes the finite Student's t-mixture models (SMMs) to describe the observation emission densities associated with each hidden state, which can be more tolerant towards outliers than conventional HMMs. Based on these two techniques, the proposed method is supposed to be more robust and can assess the performance degradation process of new objects based on data of tested objects. The superiority of the proposed approach is evaluated using the vibration data from the accelerated life tests of bearings and the public XJTU-SY Bearing Datasets. The results demonstrate the robustness and effectiveness of the proposed approach for PDA modeling of rolling element bearings. |
| topic |
Robustness performance degradation assessment student???s t-HMM nuisance attribute projection bearings |
| url |
https://ieeexplore.ieee.org/document/9032137/ |
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