Split spectrum processing and automatic flaw detection

The integrity of materials used in applications such as nuclear power plants and aircraft engines is tested periodically for defects that could potentially lead to part failures during critical operations. Ultrasonic flaw detection plays an important part in the nondestructive evaluation (NDE) of these materials. This chapter presents signal processing approaches for enhancing defect detection in materials consisting of grain-like microstructures. Grain scatterers create noise processes with properties similar to those created by flaw scatterers, which makes for a challenging detection problem. This chapter highlights a particular flaw detection approach, referred to as split-spectrum processing (SSP), and explains its performance relative to classical approaches, such as Wiener and matched filtering. Analytical and simulation results are presented to demonstrate the ways in which SSP uses statistical properties of scatterer phase spectra to enhance flaw detection. In addition, examples are included to demonstrate SSP implementations for automatic flaw detection.