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An Optimal Unknown Input Observer Based Fault Diagnosis Method

HU Zhi-Kun 1, 2 SUN Yan 1 JIANG Bin 2 HE Jing 3 ZHANG Chang-Fan 31. School of Physics and Electronics, Central South University, Changsha 410083 2. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 3. School of Electrics Engineering, Hunan University of Technology, Zhuzhou 412001  
A full-order unknown input observer (UIO) is employed for uncertain dynamic systems with unknown input interference and noise to eliminate the interference and achieve state estimation, combine with the Kalman filter algorithm to solve the state feedback matrix to minimum the covariance of the residual signal, so as to enhance the robustness of the system noise, thus an optimal unknown input observer is achieved as a residual generator. The threshold is designed based on the generalized likelihood ratio (GLR) method to evaluate the residual signals and achieve a high fault detection rate. Finally, the drive train system of the wind turbine with additive sensor faults and multiplicative sensor faults is used as an example. The residual signals are simulated and the results shows the effectiveness of the proposed method.
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