Crack detection in a pipe by adaptive subspace iteration algorithm and least square support vector regression

A new combination method of beam-type finite element multiwavelet-based algorithm and least square support vector regression (LSSVR) algorithm is proposed for detecting the location and size of a crack in a pipe. According to operators of engineering problems, Rayleigh-Euler and Rayleigh-Timoshenko beam-type multiwavelets are constructed using the stable completion in the multiresolution finite element space. A rotational spring model is used for cracked pipe modeling and the local flexibility due to the crack is calculated by discrete approximation method. An adaptive subspace iteration algorithm (ASIA) is applied to efficiently approximate the exact solution of pipe model by adding new beam-type multiwavelets in each scale. To avoid the difficulty of constructing well-defined mathematical models, the normalized crack location and depth is detected by using LSSVR algorithm. The numerical and experimental results verify that the presented method can accurately identify the location and depth of crack in a pipe.