Observer-based structural damage detection using genetic algorithm

The observer-based fault detection and isolation filter design method is a model-based method. By carefully choosing the observer gain, the residual outputs can be projected onto different independent subspaces. Each subspace corresponds to each monitored structural element, so that the projected residual will be nonzero when the associated structural element is damaged and zero when there is no damage. The key point of detection filter design is how to find an appropriate observer gain. This problem can be interpreted in a geometric framework and is found to be equivalent to the problem of finding a decentralized static output feedback gain. But it is a challenging task to find the decentralized controller by either analytical or numerical methods because its solution set is generally non-convex. In this paper, genetic algorithm is originally proposed to find the detection-filter-based decentralized controller, which can be applied in structural health monitoring. The numerical simulation and experimental results show that the developed method can successfully identify structural damage.