Closed-Loop Fault Diagnosis of SDR Using Gap Metric, PCA, and Kalman’s Principle
The measurement of the pressure in the gas generator (GG) plays a decisive role in the closed-loop regulation of the gas flow in a solid ducted rocket ramjet (SDR). Therefore, the fault detection and isolation (FDI) of the pressure sensors is particularly significant. Especially in the GG with doubl...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2023/9994093 |
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| author | Hongfu Wang Qinghua Zeng An Wang Zongyu Zhang Weide Liu |
| author_facet | Hongfu Wang Qinghua Zeng An Wang Zongyu Zhang Weide Liu |
| author_sort | Hongfu Wang |
| collection | DOAJ |
| description | The measurement of the pressure in the gas generator (GG) plays a decisive role in the closed-loop regulation of the gas flow in a solid ducted rocket ramjet (SDR). Therefore, the fault detection and isolation (FDI) of the pressure sensors is particularly significant. Especially in the GG with double pressure feedback, there are issues such as less available data and sensor fault transmission, which make the FDI more difficult. In this paper, for the GG with double pressure feedback, firstly, the “Consistency Index” was constructed based on the principal component analysis (PCA) algorithm, which made it easier to evaluate the consistency of the measured values. Secondly, based on Kalman’s principle, the redundancy information of the system was used to estimate the pressure in the GG. Finally, the gap metric between the measured pressure and the estimated pressure was employed to characterize the health of the sensors. Compared with the MWPCA algorithm, it was shown that our proposed algorithm was more accurate in fault diagnosis and could avoid the problem of missing alarm when two sensors had consistent faults, which would provide strong support for the safe operation of the SDR and could further promote its application in long-endurance aircrafts. |
| format | Article |
| id | doaj-art-ca7f9c6f26a149fba0db45200e58f2bd |
| institution | DOAJ |
| issn | 1687-5974 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-ca7f9c6f26a149fba0db45200e58f2bd2025-08-20T03:24:04ZengWileyInternational Journal of Aerospace Engineering1687-59742023-01-01202310.1155/2023/9994093Closed-Loop Fault Diagnosis of SDR Using Gap Metric, PCA, and Kalman’s PrincipleHongfu Wang0Qinghua Zeng1An Wang2Zongyu Zhang3Weide Liu4College of Aeronautics and AstronauticsCollege of Aeronautics and AstronauticsInstitute of Air and Space TechnologyCollege of Aeronautics and AstronauticsCollege of Aeronautics and AstronauticsThe measurement of the pressure in the gas generator (GG) plays a decisive role in the closed-loop regulation of the gas flow in a solid ducted rocket ramjet (SDR). Therefore, the fault detection and isolation (FDI) of the pressure sensors is particularly significant. Especially in the GG with double pressure feedback, there are issues such as less available data and sensor fault transmission, which make the FDI more difficult. In this paper, for the GG with double pressure feedback, firstly, the “Consistency Index” was constructed based on the principal component analysis (PCA) algorithm, which made it easier to evaluate the consistency of the measured values. Secondly, based on Kalman’s principle, the redundancy information of the system was used to estimate the pressure in the GG. Finally, the gap metric between the measured pressure and the estimated pressure was employed to characterize the health of the sensors. Compared with the MWPCA algorithm, it was shown that our proposed algorithm was more accurate in fault diagnosis and could avoid the problem of missing alarm when two sensors had consistent faults, which would provide strong support for the safe operation of the SDR and could further promote its application in long-endurance aircrafts.http://dx.doi.org/10.1155/2023/9994093 |
| spellingShingle | Hongfu Wang Qinghua Zeng An Wang Zongyu Zhang Weide Liu Closed-Loop Fault Diagnosis of SDR Using Gap Metric, PCA, and Kalman’s Principle International Journal of Aerospace Engineering |
| title | Closed-Loop Fault Diagnosis of SDR Using Gap Metric, PCA, and Kalman’s Principle |
| title_full | Closed-Loop Fault Diagnosis of SDR Using Gap Metric, PCA, and Kalman’s Principle |
| title_fullStr | Closed-Loop Fault Diagnosis of SDR Using Gap Metric, PCA, and Kalman’s Principle |
| title_full_unstemmed | Closed-Loop Fault Diagnosis of SDR Using Gap Metric, PCA, and Kalman’s Principle |
| title_short | Closed-Loop Fault Diagnosis of SDR Using Gap Metric, PCA, and Kalman’s Principle |
| title_sort | closed loop fault diagnosis of sdr using gap metric pca and kalman s principle |
| url | http://dx.doi.org/10.1155/2023/9994093 |
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