Pulsed Thermography Technique Research Articles

Experimental Procedure to Assess Depth and Size of Defects with Pulsed Thermography

Subsurface defects can be detected by the pulsed thermography (PT) technique analysing the raw thermal data with the application of different post-processing algorithms. In this regard, different methods, based on one-dimensional models, are used in the literature to estimate the depth and size of defects. Two of the most established methods are the thermal signal reconstruction (TSR) and the pulsed phase thermography (PPT) algorithms. These latter require a careful set up of the testing parameters such as the frame rate, the truncation window size, and the energy density to obtain an accurate estimation of both depths and sizes of defects. Even if some works have already investigated the issue of defect characterization, there are few works in which the correct procedures to obtain both the size and depth were deeply explained, above all for real components with real defects. The aim of this work is to propose a new empirical procedure to obtain depth and size estimation of the defects using the pulsed thermography technique and in particular the principal component thermography (PCT) algorithm. The proposed procedure is based on the experimental observation that exists a linear correlation between the defect contrasts and the relative aspect ratios. In this way, by means of a master specimen, a calibration curve can be obtained considering a suitable truncation window of the analysed data. Then, the size and depth of defects have been retrieved imposing threshold criteria. The procedure is quite general, and it can be also tested with other algorithms. Different experimental tests have been carried out on two materials, aluminium and glass fiber reinforced polymer (GFRP) and then the procedure has been applied and validated both on simulated (flat bottom holes) and real defects.

Thickness measurement research using transmission step-heating thermography

Pulsed thermography techniques are used most widely in quantitative evaluation applications but are limited by the specimen thickness. A thickness prediction method that uses transmission step-heating thermography is presented. A halogen lamp is used as a simple and inexpensive step-heating source. Because the halogen lamp undergoes a temperature rise process before reaching maximum output, its output differs from an ideal step function and this is the main cause of the measurement accuracy limitations. Therefore, an expression for the halogen lamp heating process is proposed. On this basis, under the halogen step-heating excitation condition, an equation for the specimen temperature rise over time is obtained. The specimen thickness is then calculated after nonlinear fitting of experimental data to the theoretical function. To evaluate the measurement accuracy of this thickness prediction method, specimens composed of different materials and with differing thicknesses were designed. All measurement errors were below 2%, demonstrating the method's high accuracy and wide applicability.

Empower parameterized generative adversarial networks using a novel particle swarm optimizer: algorithms and applications

In this paper, a novel parameterized generative adversarial network (GAN) is proposed where the parameters are introduced to enhance the performance of image segmentation. The developed algorithm is applied to the image-based crack detection problem on the thermal data obtained through the non-destructive testing process. A new regularization term, which contains three tunable hyperparameters, embedded into the objective function of the GAN in order to improve the contrast ratio of certain areas of the image so as to benefit the crack detection process. To automate the selection of the optimal hyperparameters of the GAN, a new particle swarm optimization (PSO) algorithm is put forward where a neighborhood-based velocity updating strategy is developed for the purpose of thoroughly exploring the problem space. The proposed PSO-based GAN algorithm is shown to 1) work well in detecting cracks on the thermal data generated by the eddy current pulsed thermography technique; and 2) outperforms other conventional GAN algorithms.

Comparison of Pulse Thermography (PT) and Step Heating (SH) Thermography in Non-Destructive Testing of Unidirectional GFRP Composites

Abstract This paper presents two techniques of active thermography i.e. the pulsed thermography technique and the step heating technique. The aim of this article is to compare these two techniques and present the possibilities, advantages and limitations of their use in the context of non-destructive testing of composite materials. The experimental section presents the results of tests carried out on samples of the polymer composites reinforced with glass fiber.

Study on the limit detection of defects by pulsed thermography in adhesive composite joints through computational simulation

In this paper the detection limit of lack of adhesive defects in GFRP adhesive composite joints was evaluated through a computational simulation model of active pulsed thermography technique. In this study, several simulations were carried out in order to evaluate the influence of the thickness of the collar, heating time and excitation energy on the detection limit of defects. In addition to these analyzes, it was also evaluated the reduction of the thermal contrast of the defects as a function of the thickness of the collar (depth of the defects) and thus it was possible to estimate mathematically the limit value of the thickness of the collar that allows the detection of the defects for each heating time. The results obtained showed that the pulsed thermography technique would be able to detect defects of lack of adhesive that are located up to 8.5 mm deep in this type of composite joint.

Numerical and experimental study for assessing stress in carbon epoxy composites using thermography

In recent years, the increasing use of composite materials has resulted in an increased attention for calculating residual stress in the composite structure. Meanwhile, reliable measurement and prediction of residual stress remain a challenge for studying the composite behavior. Due to the fact, that destructive methods can cause additional stress in addition to existing residual stress, the use of non-destructive methods is more reliable and efficient in the industry. This paper presents a new non-destructive method for monitoring stress changes in Carbon Fiber Reinforced Plastic (CFRP) composites using pulsed thermography technique. By the analysis of different thermal emission, it is possible to measure the stress on the epoxy layer and on the carbon fiber. Numerical models using finite elements have been used to determine the behaviour of the thermal emission from a composite component subjected to different tensile stresses. The experimental measurements have been performed to verify the numerical results. In the experiment cases in which the tensile stress is constant, some differences are observed. Whereas, the thermography measurements show a linear increase of the temperature response with rising tensile stress, the accurate temperature measurements are quite limited due to the camera's low sensitivity. The experimental results revealed that the finite element simulations obtained in the present work are capable of detecting the stress (residual stress) in the carbon fiber/epoxy composites.

A Quantitative Comparison among Different Algorithms for Defects Detection on Aluminum with the Pulsed Thermography Technique

Pulsed thermography is commonly used as a non-destructive technique for evaluating defects within materials and components. In the last few years, many algorithms have been developed with the aim to detect defects and different methods have been used for detecting their size and depth. However, only few works in the literature reported a comparison among the different algorithms in terms of the number of detected defects, the time spent in testing and analysis, and the quantitative evaluation of size and depth. In this work, starting from a pulsed thermographic test carried out on an aluminum specimen with twenty flat bottom holes of known nominal size and depth, different algorithms have been used with the aim to obtain a comparison among them in terms of signal to background contrast (SBC) and number of detected defects by analyzing different time intervals. Moreover, the correlation between SBC and the aspect ratio of the defects has been investigated. The algorithms used have been: Pulsed Phase Thermography (PPT), Slope, Correlation Coefficient (R2), Thermal Signal Reconstruction (TSR) and Principal Component Thermography (PCT). The results showed the advantages, disadvantages, and sensitivity of the various thermographic algorithms.

Pulsed thermography inspection of adhesive composite joints: computational simulation model and experimental validation

Abstract We developed a computer simulation model using finite elements for the reproduction of physical phenomena found in active pulsed thermography of GFRP adhesive tubular joints. During the manufacture of the joint, defects such as the lack of adhesive were included in order to evaluate the ability of the active pulsed thermography technique to detect this type of material and joint configuration. The experimental results obtained with the thermographic camera were compared with a numerical approximation obtained through the simulation model developed in this study using the Comsol Multiphysics ® software and, because of their similarity; it was possible to validate the computer simulation model. In both methods assessed in this study, it was only possible to detect the lack of adhesive when the thermographic test was performed from inside the joint, as, on the outer side of the joint, the defects' surfaces are at a depth greater than on the inner side.

The detection and quantification of the defects in adhesive bonded joints of the piezoelectric sensors by infrared thermographic nondestructive testing

In this paper, efficacy of pulsed thermography technique has been explored for the first time for the detection and quantification of the subsurface defects present in the rubber-encapsulated piezoelectric sensors. Initial experiments were performed on adhesively bonded joints of the rubber/Al or rubber/PZT control samples to find out an optimum acquisition time for the 3-mm rubber encapsulants. Thermographic measurements were performed in the reflection mode and acquired thermal images were analysed and processed images were described in terms of the phase images. The defective regions are identified as delamination of the adhesive joints at the interface of rubber and PZT stacks, and presence of porosity in the encapsulation in the inspected hydrophone. The defect depths of the observed anomalies were calculated empirically from the plots of the peak time of thermal contrast (tmax) maximum and thermal contrast maximum (Cmax) for a particular defect. The estimated defect depths of the prominent porosity observed in the PZT hydrophone are found nearly 1 mm from the surface.