/pdf/quantitative-characterization-of-micro-topography-a-2kb6z20ran.pdf

Quantitative characterization of micro-topography a bibliography of industrial surface metrology

The reliability of non-destructive evaluation de- pends on multitude of different factors. Consequently, it is difficult to assess the performance of the system. The only practical way to overcome this complexity and asses inspec- tion reliability is using practical trials. In practical trials the inspection is performed on a known, flawed sample and reli- ability is judged by comparing the acquired inspection result with known state of the sample. However, confirming (and demonstrating), that the practical trials and, in particular, the usedflaws are representative to postulatedinspectioncase is, at present, challenging. In this paper, the open literature is reviewed and compiled to the extent necessary for providing a starting point for confirming and demonstrating representativeness of flaws used in the practical trials. The available information on es- sential flaw parameters for various NDE techniques is re- viewed. The used measurement methods for each parameter is discussed and the available in-service data summarized. Finally, a simple procedure is proposed for confirming and demonstrating the representativeness of used flaws.

https://link.springer.com/content/pdf/10.1007%2Fs10921-011-0102-z.pdf

Crack Characteristics and Their Importance to NDE

Defects which possess rough surfaces greatly affect ultrasonic wave scattering behavior, usually reducing the magnitude of reflected signals. Understanding and accurately predicting the influence of roughness on signal amplitudes is crucial, especially in nondestructive evaluation (NDE) for the inspection of safety-critical components. An extension of Kirchhoff theory has formed the basis for many practical applications; however, it is widely recognized that these predictions are pessimistic because of analytical approximations. A numerical full-field modeling approach does not fall victim to such limitations. Here, a finite element (FE) modeling approach is used to develop a realistic methodology for the prediction of expected backscattering from rough defects. The ultrasonic backscatter from multiple rough surfaces defined by the same statistical class is calculated for normal and oblique incidence. Results from FE models are compared with Kirchhoff theory predictions and experimental measurements to establish confidence in the new approach. At lower levels of roughness, excellent agreement is observed between Kirchhoff theory, FE, and experimental data, whereas at higher values, the pessimism of Kirchhoff theory is confirmed. An important distinction is made between the total, coherent, and diffuse signals and it is observed, significantly, that the total signal amplitude is representative of the information obtained during an inspection. This analysis provides a robust basis for a less sensitive, yet safe, threshold for inspection of rough defects.

Improved detection of rough defects for ultrasonic nondestructive evaluation inspections based on finite element modeling of elastic wave scattering

Elastic model for simulating ultrasonic inspection of smooth and rough defects

All naturally occurring crack-like defects in solid structures are rough to some degree. Based on simulated array data for incident and scattered longitudinal waves from various rough cracks and the total focusing method (TFM) imaging algorithm, the effect of roughness on defect imaging and characterization is examined. The array data are simulated by using a previously validated model based on the Kirchhoff approximation to predict the rough crack scattering matrix. The scattering matrix describes the scattered field for all possible incident and scattering directions. The performance of TFM imaging for detecting rough crack-like defects is investigated by considering the averaged scattering coefficient over specified angular coverage ranges and the maximum scattered amplitude in the final image. It is shown that roughness can be either beneficial or detrimental to the detectability of a crack-like defect, depending on the defect characteristics, such as length, roughness, correlation length, orientation angle, and array inspection configuration. It is also shown that roughness can cause underestimation of the crack length if using an image-based approach for sizing.

J.A. Ogilvy

Papers

Model for the ultrasonic inspection of rough defects