LI Ming1, SHUI Ai-she1, SONG Zheng-hui1, et al. Research on GRNN-based sensor fault diagnosis[J]. 2009, 28(12): 17-20+23. DOI: 10.13873/j.1000-97872009.12.026.
Aimed at solving the challenging problem of diagnosis for sensor bias and drift faults
a novel approach of sensor fault diagnosis based on generalized regression neural network(GRNN)is proposed.The method makes full use of the closed-loop monitoring information in control system to establish multi-input and single-output GRNN observers.By comparing the outputs of the GRNN observers and the actual values of sensors
the identification strategy based on the sequence of remain residuals for sensors bias fault and drift fault is acquired and sensors on-line fault diagnosis in control system is carried out.The simulation results indicate that the approach can quickly and accurately detect
Sensor fault detection, isolation and reconstruction using nonlinear principal component analysis [J] . Mohamed-Faouzi Harkat,Salah Djelel,Noureddine Doghmane,Mohamed Benouaret. International Journal of Automation and Computing . 2007 (2)