Research on Health Condition Assessment Method for Spacecraft Power Control System Based on SVM and Cloud Model
| Autor: | Hongzheng Fang, Yi Xiong, Fan Huanzhen, Zhongdong Jiang |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Spacecraft
business.industry Computer science ComputerApplications_COMPUTERSINOTHERSYSTEMS Cloud computing Reliability engineering Power (physics) Support vector machine Electric power system Health assessment Physics::Space Physics Key (cryptography) Orbit (dynamics) Astrophysics::Earth and Planetary Astrophysics business |
| Zdroj: | 2019 Prognostics and System Health Management Conference (PHM-Paris). |
| DOI: | 10.1109/phm-paris.2019.00032 |
| Popis: | Health condition assessment method can effectively ensure the performance and health status of the key components and equipment of the spacecraft power supply system, enhance the efficiency of spacecraft in orbit. Aiming at the problems of health level classification and uncertainty mapping in the health assessment application of spacecraft power control system, the algorithm strategy of combining support vector machine (SVM) and cloud model is proposed to realize the health status measurement of spacecraft power control system. Then the implementation strategy and main processes of the algorithm are described. Finally, using the historical in-orbit operation data of a spacecraft power control system, the health status evaluation of the spacecraft power system based on SVM and cloud model is realized, and the effectiveness of the method is verified. The results show that the method can effectively evaluate the performance and health of the key equipment of the spacecraft power system. It can be used as a support for online health assessment and operational decision making of key components for spacecraft power supplies. |
| Databáze: | OpenAIRE |
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