Advanced defect detection algorithm using clustering in ultrasonic NDE

A range of materials used in industry exhibit scattering properties which limits ultrasonic NDE. Many algorithms have been proposed to enhance defect detection ability, such as the well-known Split Spectrum Processing (SSP) technique. Scattering noise usually cannot be fully removed and the remaining noise can be easily confused with real feature signals, hence becoming artefacts during the image interpretation stage. This paper presents an advanced algorithm to further reduce the influence of artefacts remaining in A-scan data after processing using a conventional defect detection algorithm. The raw A-scan data can be acquired from either traditional single transducer or phased array configurations. The proposed algorithm uses the concept of unsupervised machine learning to cluster segmental defect signals from pre-processed Ascans into different classes. The distinction and similarity between each class and the ensemble of randomly selected noise segments can be observed by applying a classification algorithm. Each class will then be labelled as 'legitimate reflector' or 'artefacts' based on this observation and the expected probability of defection (PoD) and probability of false alarm (PFA) determined. To facilitate data collection and validate the proposed algorithm, a 5MHz linear array transducer is used to collect A-scans from both austenitic steel and Inconel samples. Each pulse-echo A-scan is pre-processed using SSP and the subsequent application of the proposed clustering algorithm has provided an additional reduction to PFA while maintaining PoD for both samples compared with SSP results alone

Clutter noise reduction for phased array imaging using frequency-spatial polarity coherence

A number of materials used in industry exhibit highly-scattering properties which can reduce the performance of conventional ultrasonic NDE approaches. Moving Bandwidth Polarity Thresholding (MBPT) is a robust frequency diversity based algorithm for scatter noise reduction in single A-scan waveforms, using sign coherence across a range of frequency bands to reduce grain noise and improve Signal to Noise Ratio. Importantly, for this approach to be extended to array applications, spatial variation of noise characteristics must also be considered. This paper presents a new spatial-frequency diversity based algorithm for array imaging, extended from MBPT. Each A-scan in the full matrix capture array dataset is partitioned into a serial of overlapped frequency bands and then undergoes polarity thresholding to generate sign-only coefficients indicating possible flaw locations within each selected band. These coefficients are synthesized to form a coefficient matrix using a delay and sum approach in each frequency band. Matrices produced across the frequency bands are then summed to generate a weighting matrix, which can be applied on any conventional image. A 5MHz linear array has been used to acquire data from both austenitic steel and high nickel alloy (HNA) samples to validate the proposed algorithm. Background noise is significantly suppressed for both samples after applying this approach. Importantly, three side drilled holes and the back wall of the HNA sample are clearly enhanced in the processed image, with a mean 133% Contrast to Noise Ratio improvement when compared to a conventional TFM image

Improving the operational bandwidth of a 1-3 piezoelectric composite transducer using Sierpinski Gasket fractal geometry

Wider operational bandwidth is an important requirement of an ultrasound transducer across many applications. It has been reported mathematically that by having elements with varying length scales in the piezoelectric transducer design, the device may possess a wider operational bandwidth or a higher sensitivity compared to a conventional device. In this paper, the potential for extending the operational bandwidth of a 1-3 piezoelectric composite transducer configured in a fractal geometry, known as the Sierpinski Gasket (SG), will be investigated using finite element analysis package PZFlex (Thornton Tomasetti). Two equivalent piezocomposite designs will be simulated: a conventional 1-3 piezocomposite structure and the novel SG fractal geometry arrangement. The transmit voltage response and open circuit voltage extracted from the simulations are used to illustrate the improved bandwidth predicted from the fractal composite design

Mathematical modelling of the collapse time of an unfolding shelled microbubble

There is considerable interest at the moment on using shelled microbubbles as a transportation mechanism for localised drug delivery, specifically in the treatment of various cancers. In this report a theoretical model is proposed which predicts the collapse time of an unfolding shelled microbubble. A neo-Hookean, compressible strain energy density function is used to model the potential energy per unit volume of the shell. This is achieved by considering a reference configuration (stress free) consisting of a shelled microsphere with a hemispherical cap removed. This is then displaced angularly and radially by applying a stress load to the free edge of the shell. This forms a deformed open sphere possessing a stress. This is then used as an initial condition to model the unfolding of the shell back to its original stress free configuration. Asymptotic expansion along with the conservation of mass and energy are then used to determine the collapse times for the unfolding shell and how the material parameters influence this. The theoretical model is compared to published experimental results

Radiation properties of truncated cones to enhance the beam patterns of air-coupled transducers

Radiation properties of cones are used to steer energy from the side lobes toward the center of the beam pattern of an air-coupled source. Two structures of superposed truncated cones are designed and implemented in a finite element package to modify the beam pattern of a piston model simulating an air-coupled transducer. Results show how the energy from the sides of the beam is conveyed toward the center of it thus widening the main lobe angular domain and smoothing the beam curve. This work is intended to support methods for range estimation performed with air-coupled transducers and localization strategies with broadband ultrasonic signals, as well as to investigate mathematical relationships at the base of radiation properties of conical structures

Dynamical model of an oscillating shelled microbubble

There is considerable interest at the moment on using shelled microbubbles as a transportation mechanism for localised drug delivery, specifically in the treatment of various cancers. In this report a theoretical model is proposed which predicts the dynamics of an oscillating shelled microbubble. A neo-Hookean, compressible strain energy density function is used to model the potential energy per unit volume of the shell. The shell is then stressed by applying a series of small radially directed stress steps to the inner surface of the shell whilst setting the outer surface’s stress to zero. The spatial profiles of the Cauchy radial and angular (hoop) stresses that are created within the shell during this quasistatic inflationary process are then stored as the shelled microbubble is inflated. The shelled microbubble is then allowed to collapse by setting the stress at the inner surface to zero. The model which results is then used to predict the dynamics of the shelled microbubble as it oscillates about its equilibrium state. A linear approximation is then used to allow analytical insight into both the quasistatic inflationary and oscillating phases of the shelled microbubble. Numerical results from the full nonlinear model are produced which show the influence of the shell’s thickness, Poisson ratio and shear modulus on the rate of oscillation of the shelled microbubble and these are compared to the approximate analytical solution. The theoretical model’s collapse time is compared to published experimental results

Wavelet analysis of poorly-focused ultrasonic signal of pressure tube inspection in nuclear industry

Pressure tube fabrication and installment challenges combined with natural sagging over time can produce issues with probe alignment for pressure tube inspection of the primary circuit of CANDU reactors. The ability to extract accurate defect depth information from poorly-focused ultrasonic signals would reduce additional inspection procedures, which leads to a significant time and cost saving. Currently, the defect depth measurement protocol is to simply calculate the time difference between the peaks of the echo signals from the tube surface and the defect from a single element probe focused at the back-wall depth. When alignment issues are present, incorrect focusing results in interference within the returning echo signal. This paper proposes a novel wavelet analysis method that employs the Haar wavelet to decompose the original poorly focused A-scan signal and reconstruct detailed information based on a selected high frequency component range within the bandwidth of the transducer. Compared to the original signal, the wavelet analysis method provides additional characteristic defect information and an improved estimate of defect depth with errors less than 5%

An expert-systems approach to automatically determining flaw depth within CANDU pressure tubes

Delayed Hydride Cracking (DHC) is a crack growth mechanism that occurs in zirconium alloys, including the pressure tubes of CANDU reactors. DHC is caused by hydrogen in solution in zirconium components being diffused to any flaws present, resulting in an increased concentration of hydrogen within these flaws. An increased hydrogen concentration can lead to brittleness, followed by cracking, in high-stress regions of a pressure tube. Regular in-service ultrasonic inspection of CANDU pressure tubes aim to locate and classify any flaws that pose a potential for DHC initiation. A common approach to inspection is the use of a bespoke tool containing multiple ultrasonic transducers to ensure that each point on the pressure tube is inspected from a minimum of three angles during a scan. All flaws from within the inspected pressure tubes must be characterized prior to restarting the reactor, thus the time-consuming analysis process lies on the critical outage path. This process is manually intensive and often requires a significant amount of expert knowledge. A modular system to automatically process outage data to provide decision support to analysts has been developed. This system saves time on the critical outage path while providing repeatable and explicable measurements. Part of the analysis process requires the depth of all flaws to be measured, which is often the most time consuming stage of the analysis process. This paper describes an approach that utilizes captured analysts knowledge to perform automatic flaw depth estimation