Ground penetrating radar (GPR) may be used to detect cracks in a buried pipe. Using GPR, there are only a few techniques, such as statistical approach robust principal component analysis (RPCA). to detect cracks in buried objects. Buried nonmetallic pipe crack detection is an important application for GPR to analyze the structural health of underground pipelines. The strength of a reflected signal may be feeble from a cracked location as compared to position with respect to that from other positions of the pipe. Currently, crack detection is a challenging task, especially when the buried pipe is nonmetallic, and soil moisture varies. In this paper, the problem of crack detection in a PVC pipe using GPR is attempted. It is a challenge to detect small sized cracks in an underground PVC pipe because the GPR image is flooded with correlated background signal or clutter, and the image patterns are typically irregularly distributed. In order to efficiently detect the crack in a buried PVC pipe, a novel adaptive crack detection algorithm has been developed with the help of covariance of real GPR data and covariance of normal distributed synthetic Gaussian data. Results are evaluated and validated to show the effectiveness of crack detection algorithm.
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