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Detection, Location, And Quantification Of Structural Damage By Neural-Netprocessed Moire Profilometry, Barry G. Grossman, Frank S. Gonzalez, Joel H. Blatt, Jeffery A. Hooker

Electrical Engineering and Computer Science Faculty Publications

The development of efficient high speed techniques to recognize, locate, and quantify damage is vitally important for successful automated inspection systems such as ones used for the inspection of undersea pipelines. Two critical problems must be solved to achieve these goals: the reduction of nonuseful information present in the video image and automatic recognition and quantification of extent and location of damage. Artificial neural network processed moire profilometry appears to be a promising technique to accomplish this. Real time video moire techniques have been developed which clearly distinguish damaged and undamaged areas on structures, thus reducing the amount of extraneous …