A robust method to identify faults in correlated sensors in machine condition monitoring

We present a robust method to identify and isolate faulty sensors among a set of correlated sensors. For each sensor, we estimate the sensor a number of times, using each of the other correlated sensors separately. We use the median of these estimates as the estimate for the sensor. When up to less than half of the sensors are faulty, this method identifies the faulty sensors accurately. Since the median is used and since estimates for the same sensor as opposed to different original sensor values are used in the median, this method is very robust. The method gives much better spill-over and error recognition rates, compared to the traditional method of using the mean of the actual sensor measurements.