Automatic data interpretation and enhanced localization for inline remote field eddy current tools

University of Technology Sydney. Faculty of Engineering and Information Technology.Most of the water pipelines laid in the 20th century, in Sydney, are made of ferromagnetic materials that corrode with time. Corrosion weakens the structure of the pipes and may eventually lead to catastrophic failures. Thus, regular inspection and maintenance of critical-pipes is needed which is both costly and challenging. Non-Destructive Evaluation (NDE) technologies, such as Remote-Field Eddy-Currents (RFEC), are a cost-effective option to assess the condition of pipes. RFEC technology is based on the double-through wall phenomenon, which results in having different areas of the pipe's geometry being convoluted into the RFEC sensor measurements. Thus, the interpretation of the signal into thickness information is a challenging task. The technology is traditionally studied using Finite Element Analysis (FEA) for very simple geometries. Examples found in the literature tend to consider for instance perfect cylindrical pipes in the presence of square axisymmetric defects. In practice, these experiments do not translate well with the organic shapes generated by the corrosion, and these idealistic scenarios bypass the need for signal deconvolution. Furthermore, the behaviour of the tool in three-dimensional space is not well understood. In this thesis, FEA simulations are performed on geometries obtained from real corroded pipes. Thus, the simulations are a reflection of a realistic RFEC inspection. Based on FEA, data-driven algorithms have been designed to solve the direct and inverse problems for homogeneous materials and to solve the signal deconvolution for nonhomogeneous materials (which requires an additional piecewise linear transformation to fully solve the inverse problem), in both, the two-dimensional axisymmetric scenario and the three-dimensional scenario. These algorithms have been tested on datasets obtained through simulations, as well as, field deployment of an inspection tool. Additionally, a localisation algorithm is proposed to align the RFEC data obtained from the field inspection with laser-scan measurements used as ground truth. Finally, a methodology for automating the data analysis for the extraction of defects present in RFEC data (in terms of localisation and 2D shape segmentation) has been developed and tested with real data. As a result, a framework is proposed to process raw RFEC data and ultimately extract the location and shape of defects which will, in turn, assist with pipe failure prevention

Multiple parameters based pulsed eddy current non-destructive testing and evaluation

PhD ThesisEddy current sensing technique is widely used primarily because of its high tolerance to harsh environments, low cost, broad bandwidth and ease of automation. And its variant, pulsed eddy current offers richer information of target materials. However, accurate detection and characterisation of defects remains a major challenge in the petro-chemical industry using this technique which leads to spurious detection and false alarm. A number of parameters are contributory, amongst which is the inhomogeneity of the materials, coupling variation effect and relatively large lift-off effect due to coating layers. These sometimes concurrently affect the response signal. For instance, harsh and dynamic operating conditions cause variation in the electrical conductivity and magnetic permeability of materials. Also, there is the increased need to detect defects and simultaneously measure the coating layer. In practice therefore, multi-sensing modalities are employed for a comprehensive assessment which is often capital intensive. In contrast to this, multiple parameter delineation and estimation from a single transient response which is cost-effective becomes essential. The research concludes that multiple parameter delineation helps in mitigating the effect of a parameter of interest to improve the accuracy of the PEC technique for defect detection and characterisation on the one hand and for multi-parameter estimation on the other. This research, partly funded by the Petroleum Technology Development Fund (PTDF), proposes use of a novel multiple parameter based pulsed eddy current NDT technique to address the challenges posed by these factors. Numerical modelling and experimental approaches were employed. The study used a 3D finite element model to understand, predict and delineate the effect of varying EM properties of test materials on PEC response; which was experimentally validated. Also, experimental studies have been carried out to demonstrate the capabilities of the proposed to estimate multiple parameters vis-à-vis defect depth (invariant of lift-off effects) and lift-off. The major contributions of the research can be summarised thus: (1) numerical simulation to understand and separate the effect of material magnetic permeability and electrical conductivity in pulsed eddy current measurements and experimental validation; (2) proposed the lift-off point of intersection (LOI) feature for defect estimation invariant of lift-off effects for ferromagnetic and non-ferromagnetic samples; a feature which is hitherto not apparent in ferromagnetic materials (a primary material used in the oil and gas industry); (3) separation and estimation of defect and the lift-off effects in magnetic sensor based pulsed eddy current response; and (4) application of the LOI feature and demonstration of increased defect sensitivity of the PEC technique with the proposed feature in both ferrous and non-ferrous conductive materials.Petroleum Technology Development Fund (PTDF) for sponsoring this research work through the overseas scholarship scheme

Eddy current defect response analysis using sum of Gaussian methods

This dissertation is a study of methods to automatedly detect and produce approximations of eddy current differential coil defect signatures in terms of a summed collection of Gaussian functions (SoG). Datasets consisting of varying material, defect size, inspection frequency, and coil diameter were investigated. Dimensionally reduced representations of the defect responses were obtained utilizing common existing reduction methods and novel enhancements to them utilizing SoG Representations. Efficacy of the SoG enhanced representations were studied utilizing common Machine Learning (ML) interpretable classifier designs with the SoG representations indicating significant improvement of common analysis metrics

Investigation of wireless power transfer-based eddy current non-destructive testing and evaluation

PhD ThesisEddy current testing (ECT) is a non-contact inspection widely used as non-destructive testing and evaluation (NDT&E) of pipeline and rail lines due to its high sensitivity to surface and subsurface defects, cheap operating cost, tolerance to harsh environments, and capability of a customisable probe for complex geometric surfaces. However, the remote field of transmitter-receiver (Tx-Rx) ECT depends on the Tx-Rx coils gap, orientation, and lift-off distance, despite each coil responding to the effect of sample parameters according to its liftoff distance. They bring challenges to accurate defect detection and characterisation by weakening the ECT probe’s transfer response, affecting sensitivity to the defect, distorting the amplitude of the extracted features, and responding with fewer feature points at non-efficient energy transfer. Therefore, this study proposed a magnetically-coupled resonant wireless power transfer (WPT)-based ECT (WPTECT) concept to build the relationship between Tx-Rx coil at maximum energy transfer response, including shifting and splitting (resonance) frequency behaviour. The proposed WPTECT system was investigated in three different studies viz., (1) investigated the multiple resonance point features for detection and characterisation of slots on two different aluminium samples using a series-series (SS) topology of WPTECT; (2) mapped and scanned pipeline with a natural dent defect using a flexible printed coil (FPC) array probe based on the parallel-parallel (PP) topology of WPTECT; and (3) evaluated five different WPTECT topologies for optimal response and extracted features and characterised entire parameters of inclined angular Rolling Contact Fatigue (RCF) cracks in a rail-line material via an optimised topology. Multiple feature extraction, selection, and fusion were evaluated for the defect profile and compared in the study, unattainable by other ECT methods. The first study's contribution investigated multiple resonances and principal component analysis (PCA) features of the transfer response from scanning (eight) slots on two aluminium samples. The results have shown the potential of the multiple features for slot depth and width characterisation and demonstrated that the eddy-current density is highest at two points proportionate to the slot width. The second study's contribution provided a larger area scanning capability in a single probe amenable to complex geometrical structures like curvature surfaces. Among the extracted individual and fused features for defect reconstruction, the multi-layer feed-forward Deep learning-based multiple feature fusion has better 3D defect reconstruction, whilst the second resonances feature provided better local information than the first one for investigating pipeline dent area. The third study's contribution optimised WPTECT topology for multiple feature points capability and its optimal features extraction at the desired lift-off conditions. The PP and combined PP and SS (PS-PS) WPTECT topologies responded with multiple resonances compared to the other three topologies, with single resonance, under the same experimental situation. However, the extracted features from PS-PS topology provided the lowest sensitivity to lift-off distances and reconstructed depth, width, and inclined angle of RCF cracks with a maximum correlation, R2 -value of 96.4%, 93.1%, and 79.1%, respectively, and root-mean-square-error of 0.05mm, 0.08mm, and 6.60 , respectively. The demonstrated magnetically-coupled resonant WPTECT Tx-Rx probe characterised defects in oil and gas pipelines and rail lines through multiple features for multiple parameters information. Further work can investigate the phase of the transfer response as expected to offer robust features for material characterisation. The WPTECT system can be miniaturised using WPT IC chips as portable systems to characterise multiple layers parameters. It can further evaluate the thickness and gap between two concentric conductive tubes; pressure tube encircled by calandria tube in nuclear reactor fuel channels.PTDF Nigeri

Design of a lock-in amplifier integrated with a coil system for eddy-current non-destructive inspection

© 2017 IEEE. Eddy-current non-destructive inspections of conductive components are of great interest in several industries including civil infrastructure and the mining industry. In this work, we have used a driver-pickup coil system as the probe to carry out inspection of ferromagnetic plates. The specific geometric configuration of the probe generates weak electric signals that are buried in a noisy environment. In order to detect these weak signals, we have designed and implemented a lock-in amplifier as part of the signal processing technique to increase the signal-to-noise ratio and also improve the sensitivity of the probe. We have used Comsol as a finite element method (FEM) to design the probe and conducted experiments with the probe and the lock-in amplifier. The experimental results, which are in agreement with the FEM results, indicate that the designed probe along with a lock-in amplifier can potentially be used to estimate the thickness of thin plates