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Ultrasonic flaw detection based on temporal and subband signals applied to neural network

Ultrasonic NDE uses high frequency acoustic waves to evaluate materials, and often signal processing is required to detect echoes from defects in the presence of microstructure scattering noise. Scattering noise, also known as clutter, interferes with the flaw signal and cannot be completely eliminated by using classical signal processing methods such as band-pass filtering. In this paper, neural network (NN) is used for ultrasonic flaw echo detection using temporal data and subband signals to design and train the network. This paper also discusses the implementation of the NN algorithm on an FPGA platform using ZYNQ System-on-Chip (SoC).