Abstract:When background noise changes large, it is difficult to diagnose the failure of multi-precision redundancy sensors system. In order to address this problem, a method based on two stage Kalman filter(TSKF) is proposed. Firstly, the noise estimated by wavelets, and the sensor data is preprocessed by strong tracking Kalman filter, which is to reduce the uncertainty of observation and maximize fault information, and then it takes advantage of the redundancy to using a sensor as input, and the other sensors as output to establish the Kalman filter equations, by which the innovation obtained is used to the sensors fault diagnosis. The relationship between fault detection rate and the strength of noise is discussed by experiments, which shows that the method is robust and improve the accuracy of fault diagnosis.
谭平, 蔡自兴. 强噪声背景下的多精度传感器故障诊断[J]. 电工技术学报, 2012, 27(4): 83-87.
Tan Ping, Cai Zixing. Fault Diagnosis of Multi-Precision Sensors in Large Noise Background. Transactions of China Electrotechnical Society, 2012, 27(4): 83-87.
[1] 张娅玲, 陈伟民, 等. 传感器故障诊断技术概述[J]. 传感器与微系统, 2009, 28(1): 4-6. Zhang Yaling, Chen Weimin, et al. Overview on sensor fault diagnosis technology[J]. Transducer and Microsystem Technologies, 2009, 28(1): 4-6. [2] 黎梨苗, 陆绮荣, 徐永杰. 基于硬件冗余的传感器故障诊断研究[J]. 微计算机信息, 2008, 24(7): 211-212. Li Limiao, Lu Qirong, Xu Yongjie. Reseach of sensor fault diagnosis based on hardware redundancy[J]. Microcomputer Information, 2008, 24(7): 211-212. [3] 颜东, 张洪钺. 均值检验方法及其在冗余惯性导航系统中的应用[J]. 航空学报, 1997, 18(4): 417-42. Yan Dong, Zhang Hongyue. Mean value test method and its application for redundant navigation system[J]. Acta Aeronautica et Astronautica Sinica, 1997, 18(4): 417-42. [4] 赵志刚, 赵伟. 基于动态不确定度理论的多传感器系统传感器失效检测方法[J]. 传感技术学报, 2006, 19(6): 2723-2726. Zhao Zhigang, Zhao Wei. A new sensor failure detection method based on dynamic uncertainty theory[J]. Chinese Journal of Sensors and Actuators, 2006, 19(6): 2723-2726. [5] Jin Hong, Zhang Hongyue. Optimal parity vector sensitive to designated sensor fault[J]. IEEE Transaction on Aerospace and Electronic System, 1999, 35(4): 1122-1128. [6] Gilmore J, McKern R. A Redundant strapdown inertial reference unit(SIRU)[J]. Journal of Spacecraft and Rockets, 1972, 9(1): 39. [7] 冯志刚, 王祁, 等. 基于小波包和支持向量机的传感器故障诊断方法[J]. 南京理工大学学报 (自然科学版), 2008, 32(5): 609-614. Feng Zhigang, Wang Qi, et al. Sensor fault diagnosis based on wavelet packet and support vector machines[J]. Journal of Nanjing University of Science and Technology (Natural Science), 2008, 32(5): 609-614. [8] Namvar M, Aghili F. Failure detection and isolation in robotic manipulators using joint torque sensors[J]. Robotica, 2010, 28(4): 549- 561. [9] Castaldi P, Geri W, Bonfe M. Design of residual generators and adaptive filters for the FDI of aircraft model sensors[J]. Control Engineering Practice, 2010, 18: 449-459. [10] 赵艳菊. 强噪声背景下机械设备微弱信号的提取与检测技术研究[D]. 天津: 天津大学机械工程学院, 2009. [11] Donoho D L. Denoising by soft thresholding[J]. IEEE Transactions on Information Theory, 1995, 41(3): 613-627. [12] Donoho D L, Johnstone I. Ideal spatial adaptation by wavelet shrinkage[J]. Biometrika, 1994, 81(3): 425-455. [13] 闻新, 张洪钺. 控制系统的故障诊断与容错控制[M]. 北京: 机械工业出版社, 1998.