9:30, SPEC-L4.1
OVERVIEW OF SIGNAL PROCESSING FOR NONDESTRUCTIVE EVALUATION
S. UDPA
9:50, SPEC-L4.2
ADAPTIVE NOISE CANCELLATION SCHEMES FOR MAGNETIC FLUX LEAKAGE SIGNALS OBTAINED FROM GAS PIPELINE INSPECTION
M. AFZAL, R. POLIKAR, L. UDPA, S. UDPA
Nondestructive evaluation of the gas pipeline system is most commonly performed using magnetic flux leakage (MF L) techniques. A major segment of this network employs seamless pipes. The data obtained from MFL inspection of seamless pipes is contaminated by various sources of noise; including seamless pipe noise due to material properties of the pipe, lift -off variation of MFL sensor due to motion of the pipe and system noise due to on -board electronics. The noise can considerably reduce the detectability of defect signals in MFL data. This paper presents a new technique for improving the signal -to-noise-ratio in MFL data obtained from seamless pipes. The approach utilizes normalized least mean squares adaptive noise filtering coupled with wavelet shrinkage denoising to minimize the effects of various sources of noise. Results from application of the approach to data from field tests are presented. It is shown that the proposed algorithm is computationally efficient and data independent.
10:10, SPEC-L4.3
RECENT DEVELOPMENTS IN CONCRETE NONDESTRUCTIVE EVALUATION
N. BILGUTAY, J. POPOVICS, S. POPOVICS, M. KARAOGUZ
Concrete is a multi-phase composite material which is difficult to inspect using conventional ultrasonic techniques, including those that work well on relatively homogeneous materials such as metals. This paper summarizes recent research that makes use of signal processing techniques to overcome ultrasonic inspection difficulties in concrete. Basic findings from several new laboratory-based NDE techniques for concrete are reported. First, the application of split spectrum processing (SSP) is described. The SSP techniques obtains a frequency-diverse ensemble of narrowband signals through a filterbank and recombines them nonlinearly to improve the target visibility. Examples that demonstrate the capability of SSP to reduce coherent noise (clutter) in ultrasonic signals collected from concrete samples are presented. Next, a self-compensating procedure for practical one-sided surface wave transmission measurements on concrete structures is described. The utility of the technique is demonstrated by sensitivity to surface-opening crack depth in concrete slabs. Finally, an approach by which the setting process (stiffness change) in concrete is nondestructively monitored is described. The reflection factor of shear wave pulses at a steel-concrete interface is measured, from which the stiffness change (setting) of the concrete is inferred.
10:30, SPEC-L4.4
INVARIANCE ALGORITHMS FOR NONDESTRUCTIVE EVALUATION
S. MANDAYAM
A new class of invariant pattern recognition algorithms is required for interpreting nondestructive evaluation signals that occur during in-line inspection of components with varying material properties. This paper presents the theoretical development of these invariance algorithms and provides experimental validation of these algorithms using applications in magnetic flux leakage NDE and ultrasound NDE.
10:50, SPEC-L4.5
ULTRASONIC SCATTERER STRUCTURE CLASSIFICATION WITH THE GENERALIZED SPECTRUM
K. DONOHUE, L. HUANG
Ultrasonic back-scattered echoes resulting from the structures within a scanned object contain information of potential diagnostic value. The most common nondestructive evaluation (NDE) techniques use large-scale changes in the back-scatterer coefficients to reveal boundaries between materials with different density/elasticity properties or defects in homogenous material regions. Less common techniques consider small-scale scatterer characteristics that give rise to textures and other features not readily seen in the A-scan envelope or intensity image. This paper considers applying the generalized spectrum (GS) for classifying small-scale scatterer structures into three broad categories, diffuse, specular, and regular. The GS distinguishes between stationary (diffuse scattering) and certain classes of nonstationary processes based on a statistical characterization of the phase spectrum, and the GS can be normalized to limit variations due to frequency selectivity of the scatterers and the ultrasonic propagation path. This paper explains how the GS can be applied to classify scatterer structures over small sections of the ultrasonic A-scan and demonstrates its classification performance with simulations. The significance of the approach to NDE applications, such as flaw detection in homogenous material and material characterization in more complex material, is also discussed.
11:10, SPEC-L4.6
BLIND IMAGE RESTORATION FOR ULTRASONIC C-SCAN USING CONSTRAINED 2D-HOS
U. QIDWAI, C. CHEN
A new approach is presented in this paper to use Higher Order Statistics (HOS) to deconvolve the effects of blurring in ultrasonic C-Scans. The quantization effects of the mechanical scan-grid and due to the conversion of 1-D A-scan into one pixel on the image cause blurring. The proposed approach is completely blind to the source or the type of distortion and the formulation is purely two-dimensional. When the blurring function is modeled as an AR process, the image is restored recursively with the application of the inverse filter based on the AR estimate. A significant improvement in the image quality has been demonstrated. Especially, the edges are detected more prominently than present in the original image.