A sequential approach for fault detection and identification of vehicles´ ultrasonic parking sensors

This paper presents a sequential fault detection and identification algorithm to be applied for vehicle´s ultrasonic parking sensors. The algorithm detects a bias fault in any of the ultrasonic sensors by computing the probability of having that bias fault given a constructed measurement residual that is only a function of the measurement noise and measurement fault. A set of bias hypotheses are assumed and initially given equal alarm probability. It is assumed that only one sensor will acquire a bias at any given time. Once the probability of a hypothesis approaches 1, that hypothesis is declared as the correct hypothesis and the bias associated with the hypothesis is removed from the sensors´ reading. This study is essential to ensure accurate operation of vehicle´s ultrasonic parking sensors.