This paper presents a sequential fault detection and identification algorithm for detecting a fault in a vehicle�s ultrasonic parking\nsensors. The algorithm identifies a bias fault in any of the ultrasonic sensors by computing the probability of having that bias fault\ngiven a carefully constructed measurement residual that is only a function of the measurement noise and the possible measurement\nfault. A set of bias hypotheses is assumed and initially given equal alarm probability. It is assumed that only one sensor will acquire\na bias at any given time. Once the probability of a hypothesis approaches 1, that hypothesis is declared as the correct hypothesis\nand the bias associated with the hypothesis is removed from the sensors� reading. The accuracy and convergence characteristics\nof the proposed algorithm are verified using experimental results. This study is essential to ensure accurate operation of vehicle�s\nultrasonic parking sensors.
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