Ultrasonic Flaw Classification Using a Quasi-Pulse-Echo Technique

In solving ultrasonic flaw characterization problems, flaw type information is often needed in order to pursue succeeding tasks such as flaw sizing. In a typical inspection, the interaction of the incident ultrasonic pulse with the flaw results in a series of signal trains. A variety of signal features are extracted from these flaw signals and then used as the basis for the classification process. This classification process is made difficult by the large number of possible scattered waves. For example, typical ultrasonic signals from a planar crack-like defect consist of reflected responses, surface traveling waves, edge diffracted waves and head wave components. For a volumetric void-like defect, the returned signal pattern similarly contains reflected waves of the same mode as well as mode-converted reflections and “creeping” waves. However, in pulse-echo testing a fundamental difference exists between a crack-like flaw and a volumetric flaw that can be used for classification purposes. This difference is reflected in the fact that a significant mode-converted diffracted wave component can exist for a crack-like defect (Fig. 1(a)) which does not exist in pulse-echo testing for a volumetric defect (Fig.1(b))

Model-based signal processing techniques for ultrasonic flaw detection: simulation studies

The ultrasonic signals observed in inspection processes can often be accurately predicted by suitable measurement models. These model predictions can be used to provide important information to guide the development of subsequent signal processing algorithms. Here such a hybrid use of ultrasonic modeling and signal processing is demonstrated in the context of the problem of detecting ultrasonic flaw signals in noise. In particular, we wish to apply this hybrid methodology as an initial approach to solving the problem of detecting hard-alpha inclusions in titanium alloys

Development of Geometrical Models of Hard-Alpha Inclusions for Ultrasonic Analysis in Titanium Alloys

The engine titanium consortium is currently conducting an extensive study of the ultrasonic response and detectability of a number of naturally occurring hard-alpha defects found in titanium billets. These naturally occurring defects appear to be highly irregular in shape and inhomogeneous in composition, and we would like to access the extent to which their responses can be predicted by available ultrasonic scattering models [1]. Three dimensional geometrical (surface and solid) models of the hard-alpha defects are needed in order to obtain the geometrical and material properties to drive the ultrasonic model calculations and the subsequent probability-of-detection evaluation [2]

An exploration of the utilities of terahertz waves for the NDE of composites

We report an investigation of terahertz waves for the nondestructive evaluation of composite materials and structures. The modalities of the terahertz radiation used were time domain spectroscopy (TDS) and continuous wave (CW). The composite materials and structures investigated include both non‐conducting polymeric composites and carbon fiber composites. Terahertz signals in the TDS mode resembles that of ultrasound; however, unlike ultrasound, a terahertz pulse can detect a crack hidden behind a larger crack. This was demonstrated in thick GFRP laminates containing double saw slots. In carbon composites the penetration of terahertz waves is quite limited and the detection of flaws is strongly affected by the angle between the electric field vector of the terahertz waves and the intervening fiber directions. The structures tested in this study include both solid laminates and honeycomb sandwiches. The defects and anomalies investigated by terahertz waves were foreign material inclusions, simulated disbond and delamination, mechanical impact damage, heat damage, and water or hydraulic fluid ingression. The effectiveness and limitations of terahertz radiation for the NDE of composites are discussed

Coupling Microstructure Outputs of Process Models to Ultrasonic Inspectability Predictions

The efforts of the materials community can be characterized as the study of the relationship of processing, structure, properties and performance, as schematically illustrated in Figure 1. Added, in parentheses, are quantities of importance when these ideas are applied to ultrasonic NDE. It would be highly desirable if one could start from models of processes such as rolling, casting and extrusion; predict the microstructural features produced, such as grain size or shape, texture (preferred grain orientation), or the two-point correlation of elastic constants (to be discussed later); predict the resulting ultrasonic properties such as velocity v, attenuation a and backscattering coefficient η; and ultimately determine the inspectability of the part. Such a capability would allow NDE to be considered explicitly during the selection of material processing procedures

Signal Modeling in the Far-Infrared Region for Nondestructive Evaluation Applicatinos

Terahertz radiation (a.k.a. T‐ray) has emerged as a powerful inspection technique in recent years. It extends into the lower region of far‐infrared in the electromagnetic spectrum, and has been proven very effective in many NDE applications. T‐ray is particularly useful in some areas where accessibility is difficult or even not possible for other conventional NDE methods. Here we report a modeling effort of T‐ray signal in one such application: the detection of “hidden delamination”, a special situation that a delamination was shadowed by another. This special case was experimentally simulated by two parallel saw‐cuts in glass composites. In this paper, we also explore the feasibility of combing T‐ray and Fourier transform infrared spectroscopy using a unified least‐squares scheme for material characterization

Methodology for Estimating Nondestructive Evaluation Capability

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