An improved probabilistic diagnosis imaging algorithm for quantifying Hole-edge crack growth

Abstract

Probabilistic damage imaging (PDI) algorithm based on Lamb wave is one of the most promising structural health monitoring technologies for quantifying the hole-edge crack. However, it is still a challenge how to use a limited number of sensors to quantify the hole-edge crack. This paper proposed an improved probabilistic damage imaging algorithm (IPDI) to track the hole-edge crack growth. A simulation has been conducted to deeply study the interaction of cracks and Lamb waves. A damage index calculated by the frequency-domain energy has been found to have a good capacity for monotonically characterizing crack propagation. The further study derives a unifying relationship between damage index and the ellipse size control factor from the crack to transmitter–receiver paths with different lengths and angles. The unifying relation is used to define a new dynamic elliptical control parameter in PDI algorithm to improve the capacity of crack quantification. The improved PDI algorithm is verified by both of simulation and experiments with different exciting frequencies, whose results show that the crack imaging error of the IPDI algorithm is below 1 mm, and the accuracy is much higher than that of the traditional PDI algorithm. The proposed IPDI algorithm can effectively quantify the hole-edge crack growth.