Review and comparison of shearography and active thermography for nondestructive evaluation

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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

Development of active microwave thermography for structural health monitoring

Active Microwave Thermography (AMT) is an integrated nondestructive testing and evaluation (NDT&E) method that incorporates aspects of microwave NDT and thermography techniques. AMT uses a microwave excitation to generate heat and the surface thermal profile of the material or structure under test is subsequently measured using a thermal camera (or IR camera). Utilizing a microwave heat excitation provides advantages over traditional thermal excitations (heat lamps, etc.) including the potential for non-contact, selective and focused heating. During an AMT inspection, two heating mechanisms are possible, referred to as dielectric and induction heating. Dielectric heating occurs as a result of the interaction of microwave energy with lossy dielectric materials which results in dissipated microwave energy and a subsequent increase in temperature. Induction heating is a result of induced surface current on conductive materials with finite conductivity under microwave illumination and subsequently ohmic loss. Due to the unique properties of microwave signals including frequency of operation, power level, and polarization, as well as their interaction with different materials, AMT has strong potential for application in various industries including infrastructure, transportation, aerospace, etc. As such, this Dissertation explores the application of AMT to NDT&E needs in these important industries, including detection and evaluation of defects in single- or multi-layered fiber-reinforced polymer-strengthened cement-based materials, evaluation of steel fiber percentage and distributions in steel fiber reinforced structures, characterization of corrosion ratio on corroded reinforcing steel bars (rebar), and evaluation of covered surface cracks orientation and size in metal structures --Abstract, page iv

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

Image processing based quantitative damage evaluation in composites with long pulse thermography

Pulsed thermography is a contactless and rapid non-destructive evaluation (NDE) technique that is widely used for the inspection of fibre reinforced plastic composites. However, pulsed thermography uses expensive and specialist equipment such high-energy flash lamps to generate heat into the sample, so that alternative thermal stimulation sources are needed. Long pulse thermography was recently developed as a cost-effective solution to enhance the defect detectability in composites by generating step-pulse heat into the test sample with inexpensive quartz halogen lamps and measuring the thermal response during the material cooling down. This paper provides a quantitative comparison of long pulse thermography with traditional pulsed thermography and step heating thermography in carbon fibre and glass fibre composites with flat-bottomed holes located at various depths. The three thermographic methods are processed with advanced thermal image algorithms such as absolute thermal contrast, thermographic signal reconstruction, phase Fourier analysis and principal component analysis in order to reduce thermal image artefacts. Experimental tests have shown that principal component analysis applied to long pulse thermography provides accurate imaging results over traditional pulsed thermography and step heating thermography. Hence, this inspection technique can be considered as an efficient and cost-effective thermographic method for low thermal conductivity and low thermal response rate materials. This work is carried out within the scope of EU H2020 funded EXTREME projec

Electromagnetic Thermography Nondestructive Evaluation: Physics-based Modeling and Pattern Mining

Electromagnetic mechanism of Joule heating and thermal conduction on conductive material characterization broadens their scope for implementation in real thermography based Nondestructive testing and evaluation (NDT&E) systems by imparting sensitivity, conformability and allowing fast and imaging detection, which is necessary for efficiency. The issue of automatic material evaluation has not been fully addressed by researchers and it marks a crucial first step to analyzing the structural health of the material, which in turn sheds light on understanding the production of the defects mechanisms. In this study, we bridge the gap between the physics world and mathematical modeling world. We generate physics-mathematical modeling and mining route in the spatial-, time-, frequency-, and sparse-pattern domains. This is a significant step towards realizing the deeper insight in electromagnetic thermography (EMT) and automatic defect identification. This renders the EMT a promising candidate for the highly efficient and yet flexible NDT&E

Coating Thickness Measurements and Defect Characterization in Non-Metallic Composite Materials by Using Thermography

Thermography is a non-destructive testing method (NDT), which is widely used to guarantee the quality of non-metallic materials, such as carbon fiber composite, anti-reflection (AR) film, and coatings. As other NDT methods do, thermography determines a defective area based on the signal difference between suspected defective areas and defective-free areas. Two unavoidable effects are decreasing the credibility of thermography detection: one is uneven heating, and the other is lateral diffusion of heat. To solve this problem, researchers have developed various reconstruction methods. Restoring methods are known to have the capacity to reduce the effect of heat-flux lateral diffusion by de-convoluting a point spread function either along a temporal profile or a spatial profile to process captured thermal images. These methods either require pre-knowledge with depth or are not effective in detecting deep defects. Here we propose a spatial-temporal profile-based reconstruction method to reduce the effect of uneven heating and lateral diffusion. The method evaluates the heat flux deposited onto tested samples based on surface temperature gathered under ideal conditions. Then the proposed method is tested in three real applications – in defect detection on semi-transparent materials, on semi-infinite defects (coatings) and anisotropic materials. The method is evaluated against existing methods. Results suggest that the proposed method is effective and computationally efficiently over all the reconstruction methods reviewed. It reduces the effect of uneven heating by providing a good approximation to the input heat flux at the ending image of the sequence