Rough surface reconstruction for ultrasonic NDE simulation

Abstract

The reflection of ultrasound from rough surfaces is an important topic for the NDE of safety-critical components, such as pressure-containing components in power stations. The specular reflection from a rough surface of a defect is normally lower than it would be from a flat surface, so it is typical to apply a safety factor in order that justification cases for inspection planning are conservative. The study of the statistics of the rough surfaces that might be expected in candidate defects according to materials and loading, and the reflections from them, can be useful to develop arguments for realistic safety factors. This paper presents a study of real rough crack surfaces that are representative of the potential defects in pressure-containing power plant. Two-dimensional (area) values of the height of the roughness have been measured and their statistics analysed. Then a means to reconstruct model cases with similar statistics, so as to enable the creation of multiple realistic realizations of the surfaces, has been investigated, using random field theory. Rough surfaces are reconstructed, based on a real surface, and results for these two-dimensional descriptions of the original surface have been compared with those from the conventional model based on a one-dimensional correlation coefficient function. In addition, ultrasonic reflections from them are simulated using a finite element method.

Ultrasonic health monitoring in structural engineering: buildings and bridges

“…Ultrasound thermography uses an infrared camera to detect the thermal radiation emitted from a flaw as a result of the interaction between the elastic waves and the flaw. The roughness of the surface due to corrosion of a steel structure can be a problem in detecting corrosion with ultrasonic waves .…”

Recovery of correlation function of internal random rough surfaces from diffusely scattered elastic waves

“…For instance, tribologists are interested in efficient ways to measure surface textures, as roughness has a huge impact on friction in contact mechanics (Persson et al, 2005). In the authors' field of NDE, the 20 knowledge of surface roughness can be used for the corrosion monitoring of remotely inaccessible rough pipe walls (Jarvis and Cegla, 2012), or for the characterization of internal defect-like rough cracks (Choi et al, 2014;Zhang et al, 2011;Roberts, 2012;de Billy et al, 1980). Traditionally one can perform a point-to-point scan (Choi et al, 2014), or more advanced ultrasonic imaging 25 algorithms (Zhang et al, 2012), using the arrival time of echoes, to obtain the height data and subsequently the surface statistics.…”

“…In the authors' field of NDE, the 20 knowledge of surface roughness can be used for the corrosion monitoring of remotely inaccessible rough pipe walls (Jarvis and Cegla, 2012), or for the characterization of internal defect-like rough cracks (Choi et al, 2014;Zhang et al, 2011;Roberts, 2012;de Billy et al, 1980). Traditionally one can perform a point-to-point scan (Choi et al, 2014), or more advanced ultrasonic imaging 25 algorithms (Zhang et al, 2012), using the arrival time of echoes, to obtain the height data and subsequently the surface statistics. Unfortunately, it is difficult to accurately obtain the surface profile because the roughness significantly distorts the scattering waveforms (Zhang et al, 2012;Ogilvy, 1989).…”