Degree Type

Dissertation

Date of Award

1993

Degree Name

Doctor of Philosophy

Department

Chemical and Biological Engineering

First Advisor

William H. Brockman

Second Advisor

Satish S. Udpa

Abstract

Surface finish of an industrial part affects its ultrasonic inspection and consequently the surfaces are often machined smooth before the evaluation. Ultrasonic inspection through smooth surfaces has been well studied and understood. A theoretical basis has been established for the characterization of interior cracks, voids and inclusions, and vast amount of literature exists. However, much less is known about quantitative ultrasonic inspection of such flaws in parts with rough surfaces, e.g. machine marks or "as-cast" surfaces. A question arises "When can an industrial part with randomly rough surfaces be inspected robustly using ultrasound?" This dissertation is aimed at answering this question. It (1) develops a rigorous theory used for immersion ultrasonic inspection through randomly rough surfaces, (2) gives simple formulas suitable for engineering use, (3) consequently provides a concrete understanding of the physics of the received signal with the changes in the investigating probe's parameters as well as the statistics of the randomly rough surface, and (4) helps the development of experiments and the interpretations of measurements. Some major findings presented in this dissertation are (1) the observation of a near surface dead-zone for the flaw signal (due to substantially increased attenuation for near-surface flaws), (2) a substantial reduction in roughness-induced noise for focused probes, (3) and a consequent improvement in the signal-to-noise ratio, (4) characterization of randomly rough surfaces (the determination of surface statistics from ultrasonic reflections) and (5) comparison of the theoretical results with the available experimental measurements.

DOI

https://doi.org/10.31274/rtd-180813-10023

Publisher

Digital Repository @ Iowa State University, http://lib.dr.iastate.edu/

Copyright Owner

Mehmet Bilgen

Language

en

Proquest ID

AAI9413958

File Format

application/pdf

File Size

182 pages

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