A Novel Approach for Fault Detection in Integrated Navigation Systems
Detecting subsystem faults quickly is critical to the accuracy and reliability of integrated navigation systems. This paper, therefore, proposes an effective approach based on the novel test statistic to detect faults. Machine learning is introduced to estimate the innovation and its variance of loc...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9208713/ |
| _version_ | 1818936198395068416 |
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| author | Yixian Zhu Ling Zhou |
| author_facet | Yixian Zhu Ling Zhou |
| author_sort | Yixian Zhu |
| collection | DOAJ |
| description | Detecting subsystem faults quickly is critical to the accuracy and reliability of integrated navigation systems. This paper, therefore, proposes an effective approach based on the novel test statistic to detect faults. Machine learning is introduced to estimate the innovation and its variance of local filter. The estimates combined with the actual ones are used to construct the test statistic, which is then proved to obey chi-square distribution. Thus fault detection can be realized by chi-square test. However, the special structure of the test statistic makes it sensitive to faults, even to the gradual faults. The experimental results demonstrate that the approach can detect faults quickly. Especially for gradual fault detection, the proposed test statistic has a marked superiority compared with the traditional test statistic of residual chi-square test. |
| first_indexed | 2024-12-20T05:32:15Z |
| format | Article |
| id | doaj.art-59f3c90e16d549fb9b9b7e1bd50ad779 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T05:32:15Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-59f3c90e16d549fb9b9b7e1bd50ad7792022-12-21T19:51:42ZengIEEEIEEE Access2169-35362020-01-01817895417896110.1109/ACCESS.2020.30277539208713A Novel Approach for Fault Detection in Integrated Navigation SystemsYixian Zhu0https://orcid.org/0000-0002-5926-2043Ling Zhou1https://orcid.org/0000-0001-5076-2255Department of Materials Science and Engineering, Nantong University, Nantong, ChinaDepartment of Physics and Electronic Engineering, Yuncheng University, Yuncheng, ChinaDetecting subsystem faults quickly is critical to the accuracy and reliability of integrated navigation systems. This paper, therefore, proposes an effective approach based on the novel test statistic to detect faults. Machine learning is introduced to estimate the innovation and its variance of local filter. The estimates combined with the actual ones are used to construct the test statistic, which is then proved to obey chi-square distribution. Thus fault detection can be realized by chi-square test. However, the special structure of the test statistic makes it sensitive to faults, even to the gradual faults. The experimental results demonstrate that the approach can detect faults quickly. Especially for gradual fault detection, the proposed test statistic has a marked superiority compared with the traditional test statistic of residual chi-square test.https://ieeexplore.ieee.org/document/9208713/Fault detectionintegrated navigation systemtest statisticchi-square testKalman filter |
| spellingShingle | Yixian Zhu Ling Zhou A Novel Approach for Fault Detection in Integrated Navigation Systems IEEE Access Fault detection integrated navigation system test statistic chi-square test Kalman filter |
| title | A Novel Approach for Fault Detection in Integrated Navigation Systems |
| title_full | A Novel Approach for Fault Detection in Integrated Navigation Systems |
| title_fullStr | A Novel Approach for Fault Detection in Integrated Navigation Systems |
| title_full_unstemmed | A Novel Approach for Fault Detection in Integrated Navigation Systems |
| title_short | A Novel Approach for Fault Detection in Integrated Navigation Systems |
| title_sort | novel approach for fault detection in integrated navigation systems |
| topic | Fault detection integrated navigation system test statistic chi-square test Kalman filter |
| url | https://ieeexplore.ieee.org/document/9208713/ |
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