Infrared Thermography Nondestructive Testing Research Articles

Debonds and water-filled defects detection in honeycomb sandwich composites based on pulse infrared thermography ndt technique

Honeycomb Sandwich Composites (HSCs) have been extensively used in aerospace, automotive and shipbuilding industries due to their light weight, high temperature resistance, high strength and fatigue resistance. In this study, the infrared thermography was used to detect debonds and water-filled defects in HSCs specimens under pulsed thermal stimulation. To improve the efficiency of defects detection, dynamic thermal tomography (DTT), principal component analysis (PCA) and total harmonic distortion (THD) techniques were applied to the raw infrared image sequences. The results show that, in the inspection of HSCs, the defect identification results can be improved by using the image processing techniques mentioned above, while the signal-to-noise ratio (SNR) can be significantly improved by means of the THD technique. It is confirmed that debonds and water-filled defects in the HSCs can reliably be detected and identified by using the technique of pulse infrared thermography nondestructive testing.

Radiating power tracking based on fractional order sliding mode controller

The radiating power with sine waveform is required for modulated infrared thermography nondestructive testing. Sine voltage was applied by former authors for deriving sine power waveform. The theory mode of infrared lamp is proposed. According to numerical solution and FFT analysis, high frequency components are included in the radiating power waveform, when sine voltage is set to drive the lamp. A light intensity sensor was utilized for monitoring the real-time radiating power, and a close-loop power tracking system was constructed. Fractional order sliding mode controller was selected in the tracking system, for its robustness and flexibility property. The reachability of the controller is proved and the calculation formulas of reach time are given. In experiment, the tracking results with both PID and sliding mode controller were derived. Lower tracking overshoot and better robustness was derived through the sliding mode controller, compared with the PID counterpart.

Latest Advances in Common Signal Processing of Pulsed Thermography for Enhanced Detectability: A Review

Non-destructive testing (NDT) is a broad group of testing and analysis techniques used in science and industry to evaluate the properties of a material, structure, or system for characteristic defects and discontinuities without causing damage. Recently, infrared thermography is one of the most promising technologies as it can inspect a large area quickly using a non-contact and non-destructive method. Moreover, thermography testing has proved to be a valuable approach for non-destructive testing and evaluation of structural stability of materials. Pulsed thermography is one of the active thermography technologies that utilizes external energy heating. However, due to the non-uniform heating, lateral heat diffusion, environmental noise, and limited parameters of the thermal imaging system, there are some difficulties in detecting and characterizing defects. In order to improve this limitation, various signal processing techniques have been developed through many previous studies. This review presents the latest advances and exhaustive summary of representative signal processing techniques used in pulsed thermography according to physical principles and thermal excitation sources. First, the basic concept of infrared thermography non-destructive testing is introduced. Next, the principle of conventional pulsed thermography and signal processing technologies for non-destructive testing are reviewed. Then, we review advances and recent advances in each signal processing. Finally, the latest research trends are reviewed.

Automatic Defects Segmentation and Identification by Deep Learning Algorithm with Pulsed Thermography: Synthetic and Experimental Data

In quality evaluation (QE) of the industrial production field, infrared thermography (IRT) is one of the most crucial techniques used for evaluating composite materials due to the properties of low cost, fast inspection of large surfaces, and safety. The application of deep neural networks tends to be a prominent direction in IRT Non-Destructive Testing (NDT). During the training of the neural network, the Achilles heel is the necessity of a large database. The collection of huge amounts of training data is the high expense task. In NDT with deep learning, synthetic data contributing to training in infrared thermography remains relatively unexplored. In this paper, synthetic data from the standard Finite Element Models are combined with experimental data to build repositories with Mask Region based Convolutional Neural Networks (Mask-RCNN) to strengthen the neural network, learning the essential features of objects of interest and achieving defect segmentation automatically. These results indicate the possibility of adapting inexpensive synthetic data merging with a certain amount of the experimental database for training the neural networks in order to achieve the compelling performance from a limited collection of the annotated experimental data of a real-world practical thermography experiment.

Carbon Nanotubes Dispersion Assessment in Nanocomposites by Means of a Pulsed Thermographic Approach.

The extensive production of polymer composites reinforced by carbon nanotube is limited by the absence of non-destructive evaluation (NDE) methods capable of assessing product quality to guarantee compliance with specifications. It is well known that the level of dispersion of carbon nanotubes (CNTs) in the polymer matrix is the parameter that, much more than others, can influence their enhancement capabilities. Here an active Infrared Thermography Non Destructive Testing(IR-NDT) inspection, joined with pulsed phase thermography (PPT), were applied for the first time to epoxy-CNT composites to evaluate the level of dispersion of the nanoparticles. The PPT approach was tested on three groups of epoxy nanocomposite samples with different levels of dispersion of the nanoparticles. The phasegrams obtained with the presented technique clearly show clusters, or bundles, of CNTs when present, so a comparison with the reference sample is not necessary to evaluate the quality of the dispersion. Therefore, the new NDE approach can be applied to verify that the expected dispersion levels are met in products made from epoxy and Multi-Walled Carbon Nanotubes (MWCNTs). The mechanisms underlying the effects of the dispersion of carbon nanotube on the thermal response of polymer composites have been identified.

Development and Application of Infrared Thermography Non-Destructive Testing Techniques.

Effective testing of defects in various materials is an important guarantee to ensure its safety performance. Compared with traditional non-destructive testing (NDT) methods, infrared thermography is a new NDT technique which has developed rapidly in recent years. Its core technologies include thermal excitation and infrared image processing. In this paper, several main infrared thermography nondestructive testing techniques are reviewed. Through the analysis and comparison of the detection principle, technical characteristics and data processing methods of these testing methods, the development of the infrared thermography nondestructive testing technique is presented. Moreover, the application and development trend are summarized.

Inversion Technique for Quantitative Infrared Thermography Evaluation of Delamination Defects in Multilayered Structures

Inverse analysis is a promising tool for quantitative evaluation offering informative model-based prediction and providing accurate reconstruction results without preinspections for characterization criteria. For the traditional defect inverse reconstruction, a large number of parameters are required to reconstruct a complex defect, and the corresponding forward modeling simulation is very time-consuming. Such issues result in ill-posed and complex inverse reconstruction results, which further reduce its practical applicability. In this article, we propose and experimentally validate an inversion technique for the reconstruction of complexly shaped delamination defects in a multilayered metallic structure using signals derived from infrared thermography (IRT) testing. First, we employ a novel defect parameterization strategy based on Fourier series fitting to represent the profile of a complicated delamination defect with relatively few coefficients. Second, the multimedium element modeling method is applied to enhance a finite element method (FEM) fast forward simulator, in order to solve the mismatching mesh issue for mesh updating during inversion. Third, a deterministic inverse algorithm based on a penalty conjugate gradient algorithm is employed to realize a robust and efficient inverse analysis. By reconstructing delamination profiles with both numerically simulated IRT signals and those obtained through laser IRT experiments, the validity, efficiency, and robustness of the proposed inversion method are demonstrated for delamination defects in a double-layered plate. Based on this strategy, not only is the feasibility of the proposed method in IRT nondestructive testing is validated, but the practical applicability of inversion reconstruction analysis is significantly improved.

Independent component thermography for non-destructive testing of defects in polymer composites

Thermographic data processing and analysis is critical for effective infrared thermography non-destructive testing of defects in composite materials. In this research work, the concept of blind source separation is introduced into this field for facilitating subsurface defect detection in polymer composites. In detail, a thermal image generated by infrared thermography is viewed as a linear mixture of several independent and non-Gaussian sources, which can be decomposed by adopting the proposed independent component thermography (ICT) technique. After the decomposition, the non-Gaussian sources are extracted and plotted as a number of images with the same size as the original thermograms. Eventually, the defect signals can be separated from the non-uniform backgrounds which are usually caused by uneven heating. As a result, the location and shape information of the subsurface defective regions is highlighted. The feasibility of the ICT method is illustrated with its application to a carbon fiber reinforced polymer specimen.

Infra-Red Thermography based Inspection of Hybrid Composite Laminates under Flexure Loading

Generally, the aircraft structural parts are economically high in cost so the materials need to be inspected for defects or damages using various non-destructive testing (NDT) methods like ultrasonic, thermography and acoustic emission. The aim of this project is to characterize the defects in composite laminates before and after the flexural loading using infra-red thermography NDT method. GFRP and hybrid (GFRP+CFRP) composite laminates are fabricated with different orientation such as uni-directional, cross ply, anti-symmetric and angle ply and then tested under flexural loading according to ASTM D790 standard. The volume fraction of the fibre and matrix needs to be found out to know the void content and the mixing ratio of reinforcement and binder.

Improved image processing of road pavement defect by infrared thermography

Abstract This paper intends to achieve improved image processing for the clear identification of defects in damaged road pavement structure using infrared thermography non-destructive testing (NDT). To that goal, 4 types of pavement specimen including internal defects were fabricated to exploit the results obtained by heating the specimens by natural light. The results showed that defects located down to a depth of 3 cm could be detected by infrared thermography NDT using the improved image processing method.

Numerical simulation method for IR thermography NDE of delamination defect in multilayered plate

In this paper, a new efficient numerical method based on the finite element method (FEM) and the frequency domain summation (FDS) strategy is proposed for the simulation of the pulsed infrared thermography non-destructive testing. With use of the FDS strategy, the temperature distribution due to a pulsed thermal source is simulated based on the thermal response of series of single-frequency sinusoidal heat sources. An interpolation strategy is also adopted to reduce the necessary number of harmonic frequency responses to be calculated, and consequently the simulation time is saved. A comparison of the FDS strategy and the direct time domain integration method is also presented, which indicates that the FDS strategy can simulate pulsed thermography problem with high precision and can promote simulation efficiency.

Defect detection and evaluation of ultrasonic infrared thermography for aerospace CFRP composites

The ultrasonic infrared thermography Non-destructive Testing is introduced for detecting the impact damage of a CFRP specimen for Unmanned Aerial Vehicles. The characteristics of thermal images with damage are particularly analyzed. A Local Binary Fitting (LBF) model based on a non-Gaussian kernel function is used to segment the defect edge. In view of the discontinuity of defect in thermal images due to multilayered structure of composite materials, defect merging algorithms are proposed including time domain and space domain methods by using a few thermal images, and the defect geometric distortion during camera imaging is also compensated. The defect in the composite material can be quantitatively analyzed after the defect reconstruction. The experimental result has shown that the proposed algorithm can effectively detect and evaluate the impact damage of thermal images and the accuracy of quantitative assessment is correspondingly increased.

Research on the Application of the Infrared Thermal Image Method in Detection of Concrete Density of Concrete-Filled Steel Tube

With the extensive application of concrete-filled steel tubular structures, much attention has been paid to the detection of concrete density of the concrete-filled steel tube. Based on the advantages and research results of infrared thermography non-destructive testing, the paper established physical model and applied ANSYS finite element analysis module to numerical simulation of temperature field to make initial exploration on the applicability of such technology to the detection of concrete density of concrete-filled steel tube.

Experiments of Infrared Thermography NDT in Composite Materials with Honeycomb Sandwich Structure

To estimate the disbond defects of the carbon fiber composite materials with honeycomb sandwich structure applied in the aerospace, active infrared thermographic NDT (non-destructive testing) is researched. The specimen with known disbond defects is detected by an active infrared thermography system. The specimen is stimulated by a pulse heating source. Based on the thermal wave propagation theory, the surface temperature of the specimen contained defects will differ from the surrounding sound area because of their different thermal-physical properties. The surface temperature is monitored using infrared camera and analyzed by a computer in the time domain. The experiment results show that the active infrared thermographic NDT is rapid, effective and intuitive for detecting the disbond defects in composite materials with honeycomb sandwich structure.

Infrared Thermography Non-Destructive Testing of Composite Materials

To detect the delamination, disbond，inclusion defects of the glass fiber composite materials applied in the solid rocket motor, active infrared thermographic non-destructive testing(NDT) is researched. The samples including known defects are heated by pulsed high energy flash lamp. The surface temperature of the samples is monitored by infrared thermography camera. The results of the experiments show that the active infrared thermography technique is a fast and effective inspection method for detecting the defects of delamination, disbond，inclusion of the composites. The samples are also detected by underwater ultrasonic c-scans. The paper concludes that the active infrared thermography NDT is more suitable to rapidly detect the defect in large-area and the underwater ultrasonic c-scans is more suitable to quantitatively identify the defect in local-area.

复合材料脱粘缺陷的红外热像无损检测

复合材料脱粘缺陷的红外热像无损检测

Application of Infrared Thermography Nondestructive Testing during Wind Turbine Blade Tests

Application of Infrared Thermography Nondestructive Testing during Wind Turbine Blade Tests