Optimal Placement of Piezoelectric Actuators and Sensors for Detecting Damage in Plate Structures

Abstract

We propose a novel approach for optimal actuator and sensor placement for active sensing-based structural health monitoring. Of particular interest is the optimization of actuator—sensor arrays making use of ultrasonic wave propagation for detecting damage in thin plate-like structures. Using a detection theory framework, we establish the optimum configuration as the one that minimizes Bayes risk. The detector incorporates a statistical model of the active sensing process that accounts for both reflection and attenuation features, implements pulse-echo and pitch-catch actuation schemes, and takes into account line-of-site. The optimization space was searched using a genetic algorithm with a time-varying mutation rate. For verification, we densely instrumented a concave-shaped plate and applied artificial, reversible damage to a large number of randomly generated locations, acquiring active sensing data for each location. We then used the algorithm to predict optimal subsets of the dense array. The predicted optimal arrangements proved to be among the top performers when compared to large sets of randomly generated arrangements.