Location

La Jolla, CA

Start Date

1-1-1991 12:00 AM

Description

In ultrasonic inspections of aircraft engine components, the detectability of critical defects can be limited by grain noise. This is likely to be the case for subtle defects, such as hard-alpha-phase inclusions in titanium alloys, where the difference between the acoustic impedances of the defect and host is small. A sound quantitative description of grain noise in such alloys is essential for accurate estimates of flaw detection reliability. In this work we present a method for quantifying backscattered grain noise by using positional averaging to determine the root-mean-squared (rms) noise level. The measured noise level will depend on details of the measurement system, as well as on inherent material properties of the alloy. We present a preliminary model of the noise measurement process which accounts for system effects, and we compare its predictions with experiment. We then indicate how the rms noise data can be processed to extract a factor which parameterizes the inherent noise severity independent of the measurement process.

Book Title

Review of Progress in Quantitative Nondestructive Evaluation

Volume

10B

Chapter

Chapter 7: Characterization of Materials

Section

Properties

Pages

1663-1676

DOI

10.1007/978-1-4615-3742-7_76

Language

en

File Format

application/pdf

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Jan 1st, 12:00 AM

A Technique for Quantitatively Measuring Microstructurally Induced Ultrasonic Noise

La Jolla, CA

In ultrasonic inspections of aircraft engine components, the detectability of critical defects can be limited by grain noise. This is likely to be the case for subtle defects, such as hard-alpha-phase inclusions in titanium alloys, where the difference between the acoustic impedances of the defect and host is small. A sound quantitative description of grain noise in such alloys is essential for accurate estimates of flaw detection reliability. In this work we present a method for quantifying backscattered grain noise by using positional averaging to determine the root-mean-squared (rms) noise level. The measured noise level will depend on details of the measurement system, as well as on inherent material properties of the alloy. We present a preliminary model of the noise measurement process which accounts for system effects, and we compare its predictions with experiment. We then indicate how the rms noise data can be processed to extract a factor which parameterizes the inherent noise severity independent of the measurement process.