Sensor Fault Detection Based on Particle Filter and Mahalanobis Distance

It is essential to evaluate the health condition of structure and sensors in structural health monitoring (SHM) systems. Compared with the identification of structural damage, only a few papers investigated sensor fault detection in civil engineering. This paper presents a model-based sensor fault detection approach utilizing particle filter (PF) and Mahalanobis distance (MD). The discrete state-space model is constructed by a system identification algorithm named N4SID instead of physical principles. A sensor fault is determined if Mahalanobis distance between test state and training state is above the threshold. The experimental study demonstrates the accuracy and efficiency of the proposed method.