Crack identification using evolutionary algorithms in parallel computing environment

It is well known that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, classical optimization technique was adopted by previous researchers. That technique overcame the difficulty of finding the intersection point of the superposed contours that correspond to the eigenfrequency caused by the crack presence. However, it is hard to select the trial solution initially for optimization because the defined objective function has heavily local minima. A method is presented in this paper which uses a continuous evolutionary algorithm (CEA), which is suitable for solving inverse problems and implemented on PC clusters to shorten calculation time. With finite element model of the structure to calculate eigenfrequencies, it is possible to formulate the inverse problem in optimization format. CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on beam structures and the results are promising with high parallel efficiency over about 91%.