Remote, early-time acoustic impact Doppler inspection

Abstract

A method for nondestructive analysis is disclosed. The method includes measuring a distance between an acoustic source and each of the points to be analyzed (pixels) on the surface of an object. An optimization is then defined using the distance measurements. Thereafter, the object at each target pixel is acoustically bombarded, and the surface response at each pixel is recorded and measured. Optionally, the surface response measurements may be processed to account for extraneous information. The calculated optimization may then be used to generate the early-time line-up of the recorded measurements, and the processed information may be analyzed using the generated early-time line-up to image the internal structure object.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

The above described features and advantages of the present invention will be more fully appreciated with reference to the detailed description and figures, in which:

FIG. 1 depicts an embodiment of the preparations required before the object is impacted.

FIG. 2 depicts an embodiment of the initial processing that may be performed upon each pixel.

FIG. 3 depicts an embodiment of the follow-up processing that serves to refine and classify the information gathered from each pixel.

DETAILED DESCRIPTION

FIG. 1 depicts an embodiment of the initial stages of the method, during which the necessary preparations and calculations are accomplished. First, the surface of the object is divided, specifying the points at which the acoustic impacts will be targeted 100. These points are referred to as pixels, and the process is referred to as pixelization. In step 102, the distance between the source and each pixel is accurately determined. The calculation of an optimal observational span in step 104 for each pixel exploits the fact that the form (but not the amplitude) of the extremely-early-time response to an acoustic impact is functionally independent of location on the object, as well as the material composition of the object at a specific pixel location. Using the measurements collected in step 102, as well as the aforementioned similarity of the form of the response, an optimal observational span is calculated for each pixel. This is the time immediately following acoustic impact, when the signal from the surface response is least affected by anomalous external information. In step 106, these optimal observational spans are collected and ordered such that the early-time lineup is calculated for each pixel on the object.

Once these calculations are accomplished, the acoustic source 200, as shown in FIG. 2, generates an air-coupled pressure wave with a smoothly varying spectral content that impacts the object. The surface response is measured by a laser velocimeter 202, which also serves as a “bad shot” detector 204, determining if the pressure wave impacted the target properly. If a “bad shot” is detected, wherein the pressure wave misses the intended target, the acoustic source 200 is instructed to emit another pressure wave.

Following a successful acoustic impact at a desired location, the shot velocity signal received by the laser velocimeter is sent through filters to smooth out meaningless anomalies. In step 206, a punctured smoothing filter is applied, which is a nonlinear processing filter that smoothes out two-dimensional spikes in the data. In step 208 a simple low-pass filter is applied to filter some of the background noise inherent in the system.

FIG. 3 depicts the more advanced processing steps performed upon the signal following the determination of shot velocities 300. First, any background vibrations now present in the object are estimated as velocities 302 analogous to the velocities induced by the acoustic impact. These estimated background velocities are subtracted from the received shot velocities 304. The velocity readings have now been sufficiently processed to allow for the estimation of probable meaningful anomalous velocities, i.e. velocities that refer to some flaw or feature within the object. From this new data set, anomalous shot velocities are estimated in step 306.

In step 308, the localized background pressures are estimated at each pixel. These results are used in step 310 to normalize the amplitudes of the recorded anomalous shot velocities and to allow for accurate imaging of the interior. Finally, in step 312, this information is collected and shot velocities indicating meaningful anomalies are culled from the data set. The anomalies are divided according to physical location and segmented into pieces for analysis in step 314, resulting in an estimation of the sizes of the defects or flaws that are represented by the determined anomalies. Finally, the characteristics of the interpreted shot velocity anomalies are analyzed in step 316 to classify the anomalies, for example, in terms of the type of flaw or defect determined.

While particular embodiments have been shown and described, changes may be made to those embodiments without departing from the spirit and scope of the present invention.

Claims

1. A method for nondestructive analysis comprising: measuring a distance between an acoustic source and each of the points to be analyzed (pixels) on the surface of the object;defining an optimization using the distance measurements;acoustically bombarding the object at each target pixel;recording and measuring the object's surface response at each pixel;processing the surface response measurements to account for extraneous information;using the calculated optimization to generate the early-time line-up of the recorded measurements; andanalyzing this processed information using the generated early-time line-up to image the internal structure object.

2. The method of claim 1, wherein each pixel is acoustically bombarded a plurality of times and the results are averaged.

3. The method of claim 1, wherein the processing of the surface response comprises multiple processing steps.

4. The method of claim 3, wherein the processing is grouped into two segments, initial and follow-on processing, wherein the initial processing comprises bad shot detection, puncture filtering, and low-pass filtering of the received signals; andthe follow-on processing comprises subtracting estimated background velocities;estimating anomalous received shot velocities;normalizing the received shot velocities with respect to estimated background pressures;detecting anomalies contained within this processed data;segmenting these detected anomalies to localize them on the object; andclassifying the anomalies.

5. A method for nondestructive analysis comprising: performing initial processing and calculations upon known quantities regarding an acoustic source and an object of interest in order to specify times of interest during the acoustic bombardment of the object;acoustically bombarding the object at each target pixel;recording and measuring the object's surface response;processing the surface response measurements;detecting anomalies within the processed measurements; andclassifying the anomalies.

6. The method of claim 5, wherein the initial processing and calculations comprise measuring the distance between the acoustic source and each of the points to be analyzed (pixels) on the surface of the object and defining the distance measurements using an optimization.

7. The method of claim 5, wherein the processing of the surface response measurements comprises: detecting bad shots;low-pass filtering of the received signals;punctured smoothing of the received signals;subtracting estimated background velocities;estimating anomalous received shot velocities; andnormalizing the received shot velocities with respect to estimated background pressures.

8. The method of claim 5, wherein each pixel is acoustically bombarded a plurality of times and the results are averaged.