Wavelet-based sensor validation: Differentiating abrupt sensor faults from system dynamics

The problem of sensor fault detection is important part of the overall system health estimation. Without assuring correct sensor readings it is impossible to make any conclusion about system status. On the other hand, it is essential not to confuse sensor faults and abnormal sensor behavior caused by other reasons, such as dynamically changing system condition or fault in the system. In the current paper the problem of distinguishing between sensor faults and system dynamics is investigated. This problem cannot be solved by validating each sensor signal independently; it requires joint analysis of all sensors. The particular case of several redundant of well-correlated sensors is considered. The proposed solution consists of two steps. First, multiresolution analysis, a powerful wavelet-based signal processing technique, is applied to detect signal changes both at high and low frequency scales. Then, found changes are inspected on different wavelet detail levels and decision is made whether these changes are true sensor faults or are caused by system dynamics. The proposed method is tested on data from gas turbine power plant.