Location

Seattle, WA

Start Date

1-1-1996 12:00 AM

Description

This paper outlines a proposed methodology for using combinations of physical modeling of an inspection process along with laboratory and production data to estimate Nondestructive Evaluation (NDE) capability. The physical/statistical prediction model will be used to predict Probability of Detection (POD), Probability of False Alarm (PFA) and Receiver Operating Characteristic (ROC) function curves. These output functions are used to quantify the NDE capability. The particular focus of this work is on the use of ultrasonic methods for detecting hard-alpha and other subsurface flaws in titanium using gated peak detection. This is a uniquely challenging problem since the inspection must detect very complex subsurface flaws with significant “material” noise. However, the underlying framework of the methodology should be general enough to apply to other NDE methods.

Book Title

Review of Progress in Quantitative Nondestructive Evaluation

Volume

15B

Chapter

Chapter 8: Systems, New Techniques and Process Control

Section

Systems

Pages

1983-1990

DOI

10.1007/978-1-4613-0383-1_260

Language

en

File Format

application/pdf

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Jan 1st, 12:00 AM

Methodology for Estimating Nondestructive Evaluation Capability

Seattle, WA

This paper outlines a proposed methodology for using combinations of physical modeling of an inspection process along with laboratory and production data to estimate Nondestructive Evaluation (NDE) capability. The physical/statistical prediction model will be used to predict Probability of Detection (POD), Probability of False Alarm (PFA) and Receiver Operating Characteristic (ROC) function curves. These output functions are used to quantify the NDE capability. The particular focus of this work is on the use of ultrasonic methods for detecting hard-alpha and other subsurface flaws in titanium using gated peak detection. This is a uniquely challenging problem since the inspection must detect very complex subsurface flaws with significant “material” noise. However, the underlying framework of the methodology should be general enough to apply to other NDE methods.