Fault detection of redundant systems based on B-spline neural network

The fault detection and isolation of redundant sensor systems based on B-spline neural networks is presented in this paper. The network is trained using an algorithm with an adaptive learning rate. To further save computation time, the residual vector is transformed from a multivariate B-spline function to an univariate B-spline function. The detection of abrupt and drifting faults using the proposed method is discusses. The performance of the proposed method is illustrated by an example involving a redundant system consisting of six sensors.