Anomaly Monitoring Method for Key Components of Satellite
This paper presented a fault diagnosis method for key components of satellite, called Anomaly Monitoring Method (AMM), which is made up of state estimation based on Multivariate State Estimation Techniques (MSET) and anomaly detection based on Sequential Probability Ratio Test (SPRT). On the basis o...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/104052 |
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| _version_ | 1832549355435851776 |
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| author | Jian Peng Linjun Fan Weidong Xiao Jun Tang |
| author_facet | Jian Peng Linjun Fan Weidong Xiao Jun Tang |
| author_sort | Jian Peng |
| collection | DOAJ |
| description | This paper presented a fault diagnosis method for key components of satellite, called Anomaly Monitoring Method (AMM), which is made up of state estimation based on Multivariate State Estimation Techniques (MSET) and anomaly detection based on Sequential Probability Ratio Test (SPRT). On the basis of analysis failure of lithium-ion batteries (LIBs), we divided the failure of LIBs into internal failure, external failure, and thermal runaway and selected electrolyte resistance (Re) and the charge transfer resistance (Rct) as the key parameters of state estimation. Then, through the actual in-orbit telemetry data of the key parameters of LIBs, we obtained the actual residual value (RX) and healthy residual value (RL) of LIBs based on the state estimation of MSET, and then, through the residual values (RX and RL) of LIBs, we detected the anomaly states based on the anomaly detection of SPRT. Lastly, we conducted an example of AMM for LIBs, and, according to the results of AMM, we validated the feasibility and effectiveness of AMM by comparing it with the results of threshold detective method (TDM). |
| format | Article |
| id | doaj-art-120b8b35fbd04f8087b27ab299ed9e67 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-120b8b35fbd04f8087b27ab299ed9e672025-02-03T06:11:31ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/104052104052Anomaly Monitoring Method for Key Components of SatelliteJian Peng0Linjun Fan1Weidong Xiao2Jun Tang3College of Information Systems and Management, National University of Defense and Technology, Changsha 410073, ChinaCollege of Information Systems and Management, National University of Defense and Technology, Changsha 410073, ChinaCollege of Information Systems and Management, National University of Defense and Technology, Changsha 410073, ChinaDepartment of Telecommunications and Systems Engineering, University of Barcelona, 08202 Barcelona, SpainThis paper presented a fault diagnosis method for key components of satellite, called Anomaly Monitoring Method (AMM), which is made up of state estimation based on Multivariate State Estimation Techniques (MSET) and anomaly detection based on Sequential Probability Ratio Test (SPRT). On the basis of analysis failure of lithium-ion batteries (LIBs), we divided the failure of LIBs into internal failure, external failure, and thermal runaway and selected electrolyte resistance (Re) and the charge transfer resistance (Rct) as the key parameters of state estimation. Then, through the actual in-orbit telemetry data of the key parameters of LIBs, we obtained the actual residual value (RX) and healthy residual value (RL) of LIBs based on the state estimation of MSET, and then, through the residual values (RX and RL) of LIBs, we detected the anomaly states based on the anomaly detection of SPRT. Lastly, we conducted an example of AMM for LIBs, and, according to the results of AMM, we validated the feasibility and effectiveness of AMM by comparing it with the results of threshold detective method (TDM).http://dx.doi.org/10.1155/2014/104052 |
| spellingShingle | Jian Peng Linjun Fan Weidong Xiao Jun Tang Anomaly Monitoring Method for Key Components of Satellite The Scientific World Journal |
| title | Anomaly Monitoring Method for Key Components of Satellite |
| title_full | Anomaly Monitoring Method for Key Components of Satellite |
| title_fullStr | Anomaly Monitoring Method for Key Components of Satellite |
| title_full_unstemmed | Anomaly Monitoring Method for Key Components of Satellite |
| title_short | Anomaly Monitoring Method for Key Components of Satellite |
| title_sort | anomaly monitoring method for key components of satellite |
| url | http://dx.doi.org/10.1155/2014/104052 |
| work_keys_str_mv | AT jianpeng anomalymonitoringmethodforkeycomponentsofsatellite AT linjunfan anomalymonitoringmethodforkeycomponentsofsatellite AT weidongxiao anomalymonitoringmethodforkeycomponentsofsatellite AT juntang anomalymonitoringmethodforkeycomponentsofsatellite |