Passive low frequency RFID for non-destructive evaluation and monitoring

Ph. D ThesisDespite of immense research over the years, defect monitoring in harsh environmental conditions still presents notable challenges for Non-Destructive Testing and Evaluation (NDT&E) and Structural Health Monitoring (SHM). One of the substantial challenges is the inaccessibility to the metal surface due to the large stand-off distance caused by the insulation layer. The hidden nature of corrosion and defect under thick insulation in harsh environmental conditions may result in it being not noticed and ultimately leading to failures. Generally electromagnetic NDT&E techniques which are used in pipeline industries require the removal of the insulation layer or high powered expensive equipment. Along with these, other limitations in the existing techniques create opportunities for novel systems to solve the challenges caused by Corrosion under Insulation (CUI). Extending from Pulsed Eddy Current (PEC), this research proposes the development and use of passive Low Frequency (LF) RFID hardware system for the detection and monitoring of corrosion and cracks on both ferrous and non-ferrous materials at varying high temperature conditions. The passive, low cost essence of RFID makes it an enchanting technique for long term condition monitoring. The contribution of the research work can be summarised as follows: (1) implementation of novel LF RFID sensor systems and the rig platform, experimental studies validating the detection capabilities of corrosion progression samples using transient feature analysis with respect to permeability and electrical conductivity changes along with enhanced sensitivity demonstration using ferrite sheet attached to the tag; (2) defect detection using swept frequency method to study the multiple frequency behaviour and further temperature suppression using feature fusion technique; (3) inhomogeneity study on ferrous materials at varying temperature and demonstration of the potential of the RFID system; (4) use of RFID tag with ceramic filled Poly-tetra-fluoro-ethyulene (PTFE) substrate for larger applicability of the sensing system in the industry; (5) lift-off independent defect monitoring using passive sweep frequency RFID sensors and feature extraction and fusion for robustness improvement. This research concludes that passive LF RFID system can be used to detect corrosion and crack on both ferrous and non-ferrous materials and then the system can be used to compensate for temperature variation making it useful for a wider range of applications. However, significant challenges such as permanent deployment of the tags for long term monitoring at higher temperatures and much higher standoff distance, still require improvement for real-world applicability.Engineering and Physical Sciences Research Council (EPSRC) CASE, National Nuclear Laboratory (NNL)

Eddy current pulsed thermography for non-destructive evaluation of carbon fibre reinforced plastic for wind turbine blades

PhD ThesisThe use of Renewable energy such as wind power has grown rapidly over the past ten years. However, the poor reliability and high lifecycle costs of wind energy can limit power generation. Wind turbine blades suffer from relatively high failure rates resulting in long downtimes. The motivation of this research is to improve the reliability of wind turbine blades via non-destructive evaluation (NDE) for the early warning of faults and condition-based maintenance. Failure in wind turbine blades can be categorised as three types of major defect in carbon fibre reinforced plastic (CFRP), which are cracks, delaminations and impact damages. To detect and characterise those defects in their early stages, this thesis proposes eddy current pulsed thermography (ECPT) NDE method for CFRP-based wind turbine blades. The ECPT system is a redesigned extension of previous work. Directional excitation is applied to overcome the problems of non-homogeneous and anisotropic properties of composites in both numerical and experimental studies. Through the investigation of the multiple-physical phenomena of electromagnetic-thermal interaction, defects can be detected, classified and characterised via numerical simulation and experimental studies. An integrative multiple-physical ECPT system can provide transient thermal responses under eddy current heating inside a sample. It is applied for the measurement and characterisation of different samples. Samples with surface defects such as cracks are detected from hot-spots in thermal images, whereas internal defects, like delamination and impact damage, are detected through thermal or heat flow patterns. For quantitative NDE, defect detection, characterisation and classification are carried out at different levels to deal with various defect locations and fibre textures. Different approaches for different applications are tested and compared via samples with crack, delamination and impact damage. Comprehensive transient feature extraction at the three different levels of the pixel, local area and pattern are developed and implemented with respect to defect location in terms of the thickness and complexity of fibre texture. Three types of defects are detected and classified at those three levels. The transient responses at pixel level, flow patterns at local area level, and principal or independent components at pattern level are derived for defect classification. Features at the pixel and local area levels are extracted in order to gain quantitative information about the defects. Through comparison of the performance of evaluations at those three levels, the pixel level is shown to be good at evaluating surface defects, in particular within uni- directional fibres. Meanwhile the local area level has advantages for detecting deeper defects such as delamination and impact damage, and in specimens with multiple fibre orientations, the pattern level is useful for the separation of defective patterns and fibre texture, as well as in distinguishing multiple defects.Engineering and Physical Sciences Research Council(EPSRC), Frame Programme 7(FP7

Multi-layer carbon fiber reinforced plastic characterization and reconstruction using eddy current pulsed thermography

Ph. D. Thesis.Carbon fibre composite materials are widely used in high-value, high-profit applications, such as aerospace manufacturing and shipbuilding – due to their low density, high mechanical strength, and flexibility. Existing NDT techniques such as eddy current testing suffers from electrical anisotropy in CFRP (carbon fibre reinforced plastics). Ultrasonic is limited by substantial attenuation of signal caused by the multilayer structure. The eddy current pulsed thermography has previously been applied for composites NDE (non-destructive evaluation)such as impact damage, which has the ability for quick and accurate QNDE(quantitative non-destructive evaluation) inspection but can be challenging for detection and evaluation of sub-surface defects, e.g., delamination and debonding in multiple layer structures. Developing QNDE solutions using eddy current thermography for addressing subsurface defects evaluation in multi-layer and anisotropic CFRP is urgently required. This thesis proposes the application of eddy current pulsed thermography (ECPT) and ECPuCT (eddy current pulse compression thermography) for tackling the challenges of anisotropic properties and the multi-layer structure of CFRP using feature-based and reconstruction-based QNDE and material characterisation. The major merit for eddy current heating CFRP is the volumetric heating nature enabling subsurface defect detectability. Therefore, the thesis proposes the investigation of different ECPT and their features for QNDE of various defects, including delamination and debonding. Based on the proposed systems and QNDE approach, three case studies are implemented for delamination QNDE, debonding QNDE, conductivity estimation and orientation inverse reconstruction using the two different ECPT systems and features, e.g., a pulse compression approach to increase the capability of the current ECPT system, the feature-based QNDE approach for defect detection and quantification, and reconstruction-based approach for conductivity estimation and inversion. The three case studies include 1) investigation of delamination with different depths in terms of delamination location, and depth quantification using K-PCA, proposed temporal feature-crossing point feature and ECPuCT system; 2) investigation of debonding with different electrical and thermal properties in terms of non-uniform heating pattern removal and properties QNDE using PLS approaches, impulse response based feature

Radio frequency non-destructive testing and evaluation of defects under insulation

PhD ThesisThe use of insulation such as paint coatings has grown rapidly over the past decades. However, defects and corrosion under insulation (CUI) still present challenges for current non-destructive testing and evaluation (NDT&E) techniques. One of such challenges is the large lift-off introduced by thick insulation layer. Inaccessibility due to insulation leads corrosion and defects to be undetected, which can lead to catastrophic failure. Furthermore, lift-off effects due to the insulation layers reduce the sensitivities. The limitations of existing NDT&E techniques heighten the need for novel approaches to the characterisation of corrosion and defects under insulation. This research project is conducted in collaboration with International Paint®, and a radio frequency non-destructive evaluation for monitoring structural condition is proposed. High frequency (HF) passive RFID in conjunction with microwave NDT is proposed for monitoring and imaging under insulation. The small-size, battery-free and cost-efficient nature of RFID makes it attractive for long-term condition monitoring. To overcome the limitations of RFID-based sensing system such as effective monitoring area and lift-off tolerance, microwave NDT is proposed for the imaging of larger areas under thick insulation layers. Experimental studies are carried out in conjunction with specially designed mild steel sample sets to demonstrate the detection capabilities of the proposed systems. The contributions of this research can be summarised as follows. Corrosion detection using HF passive RFID-based sensing and microwave NDT is demonstrated in experimental feasibility studies considering variance in surface roughness, conductivity and permeability. The lift-off effects introduced by insulation layers are reduced by applying feature extraction with principal component analysis and non-negative matrix factorisation. The problem of thick insulation layers is overcome by employing a linear sweep frequency with PCA to improve the sensitivity and resolution of microwave NDT-based imaging. Finally, the merits of microwave NDT are identified for imaging defects under thick insulation in a realistic test scenario. In conclusion, HF passive RFID can be adapted for long term corrosion monitoring of steel under insulation, but sensing area and lift-off tolerance are limited. In contrast, the microwave NDT&E has shown greater potential and capability for monitoring corrosion and defects under insulation

Modelling and experimental investigation of eddy current distribution for angular defect characterisation

Current industrial requirements for nondestructive testing demand defect quantification rather than simple defect detection. This is not a simple task as defects in components, such as cracks, rarely have a simple geometrical shape. Therefore, the influence of defect shape and orientation and its effect on the inspection results needs to be addressed to avoid misinterpretation of the response signals and for a quantitative characterisation of defects. Finite element method (FEM) numerical simulations for eddy current non-destructive evaluation (ECNDE) can provide information on how the induced eddy current interacts with defects and the effect of defect shape and geometry towards the results. Through the analysis of the simulation results, links can be established between the measurements and information relating to the defect, such as 3-D shape, size and location, which facilitates not only forward problem but also inverse modelling involving experimental system specification and configuration; and pattern recognition for 3-D defect information. This work provides a study of the characterisation of angular defects through the technique of visualisation and mapping of magnetic field distribution for pulsed eddy current (PEC) and temperature distribution for PEC thermography. 3-D FEM simulations are utilised to provide the guidelines for experimental designs and specifications; understanding of the underlying physics surrounding a particular defect; and means for features extraction from the acquired responses. Through the study, defect Quantitative Non-destructive Evaluation (QNDE) has been established using the features extracted from the mapping by taking into consideration the angular characteristic of defect in the inspection results. Experimental investigations are then performed to verify the simulation results and the feasibility of the proposed techniques and extracted features to be used in acquiring information about the angular defect. The work concludes that the technique of mapping the resultant distribution from the interaction of eddy currents and defects has provided the vital information needed for defect characterisation. Features extracted from the mapping via numerical investigations have provided the means for the QNDE of angular defects. The work shows that the technique and features introduced has provided an alternative way for defect characterisation and QNDE, which also can be extended its application to other industrial components and research field.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

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

Automated Defect Detection and Characterization on Pulse Thermography Images Using Computer Vision Techniques

Defect detection and characterization plays a vital role in predicting the life span of materials. Defect detection using appropriate inspection technologies at various phases has gained huge importance in metal production lines. It can be accomplished through wise application of non-destructive testing and evaluation (NDE). It is important to characterize defects at an early stage in order to be able to overcome them or take corrective measures. Pulse thermography is a modern NDE method that can be used for defect detection in metal objects. Only a limited amount of work has been done on automated detection and characterization of defects due to thermal diffusion. This paper proposes a system for automatic defect detection and characterization in metal objects using pulse thermography images as well as various image processing algorithms and mathematical tools. An experiment was carried out using a sequence of 250 pulse thermography images of an AISI 316 L stainless steel sheet with synthetic defects. The proposed system was able to detect and characterize defects sized 10 mm, 8 mm, 6 mm, 4 mm and 2 mm with an average accuracy of 96%, 95%, 84%, 77%, 54% respectively. The proposed technique helps in the effective and efficient characterization of defects in metal objects

Multidimensional Tensor-Based Inductive Thermography With Multiple Physical Fields for Offshore Wind Turbine Gear Inspection

Condition monitoring (CM), fault diagnosis (FD), and nondestructive testing (NDT) are currently considered crucial means to increase the reliability and availability of wind turbines. Many research works have focused on CM and FD for different components of wind turbine. Gear is typically used in a wind turbine. There is insufficient space to locate the sensors for long-term monitoring of fatigue state of gear, thus, offline inspection using NDT in both manufacturing and maintenance processes are critically important. This paper proposes an inductive thermography method for gear inspection. The ability to track the properties variation in gear such as electrical conductivity, magnetic permeability, and thermal conductivity has promising potential for the evaluation of material state undertaken by contact fatigue. Conventional thermography characterization methods are built based on single physical field analysis such as heat conduction or in-plane eddy current field. This study develops a physics-based multidimensional spatial-transient-stage tensor model to describe the thermo optical flow pattern for evaluating the contact fatigue damage. A helical gear with different cycles of contact fatigue tests was investigated and the proposed method was verified. It indicates that the proposed methods are effective tool for gear inspection and fatigue evaluation, which is important for early warning and condition-based maintenance