Sensor fault diagnosis for fast steering mirror system based on Kalman filter

2015 ◽  
Author(s):  
Hongju Wang ◽  
Qiliang Bao ◽  
Haifeng Yang ◽  
Sunjie Tao
2014 ◽  
Vol 54 ◽  
pp. 494-505 ◽  
Author(s):  
R. Saravanakumar ◽  
M. Manimozhi ◽  
D.P. Kothari ◽  
M. Tejenosh

2014 ◽  
Vol 687-691 ◽  
pp. 270-274 ◽  
Author(s):  
Feng Tian ◽  
Jian Yang Zheng ◽  
Tong Zhang

The fault diagnosis of unmanned aerial vehicle (UAV) flight control system is an important research of UAV in health management. The sensor is the link which easiest to have problems of the flight control system. Making timely and accurate prediction of its faults is particularly important. A strong tracking Kalman Filter method for the sensor fault diagnosis of UAV flight control system was presented in this paper. The parameters of the system were extended to the state variables, the sensor fault observer was constructed, and the joint estimation of states and parameters of flight control system were gotten. The method can be used to real-time estimate the unmeasured states and time-varying parameters. The results of simulation experiments show that the method has a good real-time and accuracy in the sensor fault diagnosis of flight control system.


2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Dianzhu Gao ◽  
Jun Peng ◽  
Yunyou Lu ◽  
Rui Zhang ◽  
Yingze Yang ◽  
...  

Normal operation of the pressure sensor is important for the safe operation of the locomotive electro-pneumatic brake system. Sensor fault diagnosis technology facilitates detection of sensor health. However, the strong nonlinearity and variable process noise of the brake system make the sensor fault diagnosis become challenging. In this paper, an adaptive unscented Kalman filter- (UKF-) based fault diagnosis strategy is proposed, aimed at detecting bias faults and drift faults of the equalizing reservoir pressure sensor in the brake system. Firstly, an adaptive UKF based on the Sage-Husa method is applied to accurately estimate the pressure transients in the equalizing reservoir of the brake system. Then, the residual is generated between the estimated pressure by the UKF and the measured pressure by the sensor. Afterwards, the Sequential Probability Ratio Test is used to evaluate the residual so that the incipient and gradual sensor faults can be diagnosed. An experimental prototype platform for diagnosis of the equalizing reservoir pressure control system is constructed to validate the proposed method.


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