Flaw characterization in ultrasonic non-destructive testing method using exponential modeling

Abstract

Determining the shape, area, volume, and direction of flaws using ultrasonic imaging of metallic pieces, is a method estimating the severity of their defects. Different methods are used to process ultrasound images. Among these methods are spectral analyses, statistical, mathematical and intelligent methods. Within each of these, there are some advantages as well as limitations. Prony algorithm, which has been used as a parametric method for extracting exponential components of a signal, has several applications in signal modeling, system identification and classification. In this paper, after simulating pieces of oil pipeline, digital Wavelet transform has been used to reduce the noise of simulated images. Then the two dimensional Prony algorithm is applied to the images. After estimating the poles and residue of the signal using the Prony method, some features are extracted from these components in order to detect and classify defects. The method proposed in this paper, unlike conventional methods, will not only locate a flaw position in the image, but it can also be used to simultaneously estimate the depth and area of the defect.

A review of nondestructive examination technology for polyethylene pipe in nuclear power plant

“…Considering that different types of defects have different failure modes and effects on pipeline safety, recognizing the type of detected flaw is crucial for further evaluation [28]. To improve defect recognition accuracy and realize in-service inspection, automatic defect recognition technique was developed [29].…”