Location

Brunswick, ME

Start Date

1-1-1990 12:00 AM

Description

In ultrasonic nondestructive evaluation, experimental measurements of the scattered wave field resulting from sonification of a flaw are corrupted with acoustic noise. Acoustic noise results from non-flaw related scattering or reflection of the incident waves. In many probabilistic approaches to flaw detection, classification, and characterization, a stochastic model for a noise-corrupted flaw signal is utilized where acoustic noise is assumed to be an uncorrelated, Gaussian random variable with zero mean. In addition, it is assumed that an estimate of the average power spectra of the noise is available [1–3]. The goal of the work presented here was to measure and analyze acoustic noise as a random variable. Emphasis was placed on evaluating these assumptions and on estimating the average power spectra of the noise.

Book Title

Review of Progress in Quantitative Nondestructive Evaluation

Volume

9A

Chapter

Chapter 3: Interpretive Signal and Image Processing

Section

A: Signal Processing and Neural Networks

Pages

625-632

DOI

10.1007/978-1-4684-5772-8_78

Language

en

File Format

application/pdf

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Jan 1st, 12:00 AM

The Measurement and Analysis of Acoustic Noise as a Random Variable

Brunswick, ME

In ultrasonic nondestructive evaluation, experimental measurements of the scattered wave field resulting from sonification of a flaw are corrupted with acoustic noise. Acoustic noise results from non-flaw related scattering or reflection of the incident waves. In many probabilistic approaches to flaw detection, classification, and characterization, a stochastic model for a noise-corrupted flaw signal is utilized where acoustic noise is assumed to be an uncorrelated, Gaussian random variable with zero mean. In addition, it is assumed that an estimate of the average power spectra of the noise is available [1–3]. The goal of the work presented here was to measure and analyze acoustic noise as a random variable. Emphasis was placed on evaluating these assumptions and on estimating the average power spectra of the noise.