Intelligent Evaluation of Crack detection with Laser Ultrasonic technique

Abstract

In this paper, an intelligent evaluation method is proposed to quantitatively characterize surface-breaking cracks based on laser ultrasonic technique and the quantized particle swarm optimized support vector regression algorithm. Based on the physical model analysis, interactions between laser-generated surface acoustic waves (SAWs) and different cracks is numerically investigated. By selecting crucial features of the transmissions and reflections after interacting with cracks, the crack depth is evaluated with the optimized algorithm. To verify the proposed method, experimental datasets containing twelve different depths were used to size the surface-breaking cracks with incomplete prior knowledge. Evaluation results showed the high accuracy of the proposed evaluations, demonstrating the feasibility of this intelligent method for various applications in industry.