A detection method for the random noise failure of MEMS gyros on orbit
The extended Kalman filter and parity vector method are combined to optimize the gyros fault diagnosis model, compensate the constant drift, and increase the time window to improve the fault decision function. The improved model retains the ability to detect the abnormal drift faults and it can effectively detect the abnormal noise fault to isolate the fault type for the application of MEMS on orbit. The algorithm model of real satellite attitude control system is used to make the simulation verification and the results show that the system can effectively detect and isolate the fault type in a short time.
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Keywords
Micro-Electro-Mechanical System (MEMS) Gyros, random noise, Extended Kalman filter (EKF), parity vector, fault judgementAuthors
| Name | Organization | |
| muxia_l@mail.nwpu.edu.cn | ||
| lisihai@nwpu.edu.cn | ||
| wzhmwz@163.com | ||
| yaozhuoran_l@163.com |
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