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Sensor Fault Diagnosis for Fast Steering Mirror System Based on Kalman Filter
Wang Hongju; Bao Qiliang; Yang Haifeng; Tao Sunjie
Volume9676
Pages96760B
2015
Language英语
ISSN0277-786X
DOI10.1117/12.2197801
Indexed BySCI
Subtype会议论文
AbstractIn this paper, to improve the reliability of a two-axis fast steering mirror system with minimum hardware consumption, a fault diagnosis method based on Kalman filter was developed. The dynamics model of the two-axis FSM was established firstly, and then the state-space form of the FSM was adopted. A bank of Kalman filters for fault detection was designed based on the state-space form. The effects of the sensor faults on the innovation sequence were investigated, and a decision approach called weighted sum-squared residual (WSSR) was adopted to isolate the sensor faults. Sensor faults could be detected and isolated when the decision statistics changed. Experimental studies on a prototype system show that the faulty sensor can be isolated timely and accurately. Meanwhile, the mathematical model of FSM system was used to design fault diagnosis scheme in the proposed method, thus the consumption of the hardware and space is decreased.; In this paper, to improve the reliability of a two-axis fast steering mirror system with minimum hardware consumption, a fault diagnosis method based on Kalman filter was developed. The dynamics model of the two-axis FSM was established firstly, and then the state-space form of the FSM was adopted. A bank of Kalman filters for fault detection was designed based on the state-space form. The effects of the sensor faults on the innovation sequence were investigated, and a decision approach called weighted sum-squared residual (WSSR) was adopted to isolate the sensor faults. Sensor faults could be detected and isolated when the decision statistics changed. Experimental studies on a prototype system show that the faulty sensor can be isolated timely and accurately. Meanwhile, the mathematical model of FSM system was used to design fault diagnosis scheme in the proposed method, thus the consumption of the hardware and space is decreased.
Conference NameAOPC 2015: OPTICAL DESIGN AND MANUFACTURING TECHNOLOGIES
Conference Date2015
Citation statistics
Document Type会议论文
Identifierhttp://ir.ioe.ac.cn/handle/181551/7416
Collection光电工程总体研究室(一室)
Recommended Citation
GB/T 7714
Wang Hongju,Bao Qiliang,Yang Haifeng,et al. Sensor Fault Diagnosis for Fast Steering Mirror System Based on Kalman Filter[C],2015:96760B.
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