Sequential niching particle swarm optimization algorithm for localization of multiple damage locations using fiber bragg grating sensors

Structural Health Monitoring (SHM) systems have a potential to reduce lifecycle costs of structures through maintenance planning and lifetime extension. Hence, there is a lot of active research in the area for SHM of civil and mechanical structures. The SHM system should be low cost, suitable for continuous monitoring, able to detect small levels of damage. Guided waves (GW) based SHM techniques allow monitoring of large thin-walled structures with a few sensors and have been identified as the most promising of techniques for SHM. The GW based techniques allow mapping of damage very easily, and hence are a powerful tool for assessing the damage. The mapping of damage with high resolution is of course computationally expensive and hinders real-time decision making. Hence, methods are being developed to minimize the processing time. In this paper, the authors implement a sequential niching particle swarm optimization (PSO) for multiple damage detection. It is shown that the niching PSO is able to detect multiple damage scenarios effectively. The processing time is significantly better (order of magnitude) hence making it suitable for real-time assessment. The paper also presents some sensitivity studies, for determination of the thresholds. The validation has been conducted experimentally on an aluminum plate instrumented with piezo-actuators for actuation and FBG sensor for sensing. The results indicate that the niching PSO is suitable and indeed a better alternative than the brute-force techniques commonly used in literature.