Embedded linear classifiers on wireless sensor networks for damage detection

Damage detection on engineered systems is a challenging task that has been explored by numerous researchers. In recent years wireless sensors systems have arisen as a vehicle for low-power, low-cost, and localized damage detection that can be applied to various structural systems. Such sensors, however, are limited in their computational capacity and as a result, careful consideration must be taken as to which algorithms can be effectively embedded so as to balance energy constraints with computational efficiency. In this study, two classifier algorithms (least squares classifier and Fisher's linear discriminant analysis) are explored for detecting damage on a cooling system test bed. In particular, the algorithms are used to determine the valve configuration of the system and to verify if damage exists within the valves. To validate the efficiency of the algorithms in the embedded domain, the algorithms are implemented on a wireless sensing network and used to classify the system state of the test bed.