Thermography System Research Articles

Application of Unmanned Aerial Vehicles Integrated with Infrared Thermography System to Investigate the Health of Heritage Buildings

Application of Unmanned Aerial Vehicles Integrated with Infrared Thermography System to Investigate the Health of Heritage Buildings

Development of a high-speed small-angle infrared thermography system in EAST.

A high-speed infrared small-angle infrared thermography system (SATS) has been developed and installed on the Experimental Advanced Superconducting Tokamak (EAST) for measuring the surface temperature of the divertor target to calculate the high heat flux induced by Edge Localized Modes (ELMs) and providing observation means for the further physical study of some key parameters, such as power decay length λq and the characteristic time of different types of ELMs. An endoscopic optical system is applied to realize the SATS for clear imaging of the divertor plate area and protection from the harm of impurity deposition and latent tungsten ablation during discharge. The field of view (FOV) of the endoscopic optical system is designed to be 13° in the horizontal direction and 9° in the vertical direction. As a consequence, ∼35° of coverage of the lower-outer divertor and a small part of the lower-inner divertor in toroidal are covered by the FOV with a spatial resolution of around 2 mm/pixel. This paper presents a detailed description of the new SATS and the preliminary experimental diagnostic results. The radial distribution of heat flux induced by an ELM crash was demonstrated.

Spectral analysis of laser speckle contrast imaging and infrared thermography to assess skin microvascular reactive hyperemia.

Post-occlusive reactive hyperemia (PORH) test with signal spectral analysis coupled provides potential indicators for the assessment of microvascular functions. The objective of this study is to investigate the variations of skin blood flow and temperature spectra in the PORH test. Furthermore, to quantify the oscillation amplitude response to occlusion within different frequency ranges. Ten healthy volunteers participated in the PORH test and their hand skin temperature and blood flow images were captured by infrared thermography (IRT) and laser speckle contrast imaging (LSCI) system, respectively. Extracted signals from selected areas were then transformed into the time-frequency space by continuous wavelet transform for cross-correlation analysis and oscillation amplitude response comparisons. The LSCI and IRT signals extracted from fingertips showed stronger hyperemia response and larger oscillation amplitude compared with other areas, and their spectral cross-correlations decreased with frequency. According to statistical analysis, their oscillation amplitudes in the PORH stage were obviously larger than the baseline stage within endothelial, neurogenic, and myogenic frequency ranges (p<0.05), and their quantitative indicators of oscillation amplitude response had high linear correlations within endothelial and neurogenic frequency ranges. Comparisons of IRT and LSCI techniques in recording the reaction to the PORH test were made in both temporal and spectral domains. The larger oscillation amplitudes suggested enhanced endothelial, neurogenic, and myogenic activities in the PORH test. We hope this study is also significant for investigations of response to the PORH test by other non-invasive techniques.

Literature Review on Technological Applications to Monitor and Evaluate Calves' Health and Welfare.

Precision livestock farming (PLF) research is rapidly increasing and has improved farmers' quality of life, animal welfare, and production efficiency. PLF research in dairy calves is still relatively recent but has grown in the last few years. Automatic milk feeding systems (AMFS) and 3D accelerometers have been the most extensively used technologies in dairy calves. However, other technologies have been emerging in dairy calves' research, such as infrared thermography (IRT), 3D cameras, ruminal bolus, and sound analysis systems, which have not been properly validated and reviewed in the scientific literature. Thus, with this review, we aimed to analyse the state-of-the-art of technological applications in calves, focusing on dairy calves. Most of the research is focused on technology to detect and predict calves' health problems and monitor pain indicators. Feeding and lying behaviours have sometimes been associated with health and welfare levels. However, a consensus opinion is still unclear since other factors, such as milk allowance, can affect these behaviours differently. Research that employed a multi-technology approach showed better results than research focusing on only a single technique. Integrating and automating different technologies with machine learning algorithms can offer more scientific knowledge and potentially help the farmers improve calves' health, performance, and welfare, if commercial applications are available, which, from the authors' knowledge, are not at the moment.

Progress of Gamma Ray Irradiation Experiments on ITER Diagnostics from JADA

The Japan domestic agency (JADA) is responsible for procuring five diagnostic systems for ITER: the microfission chamber (MFC), poloidal polarimeter (PoPola), edge Thomson scattering (ETS), divertor impurity monitor (DIM), and divertor infrared thermography (IRTh) systems. Components of these systems that will be installed in high radiation zones must undergo radiation resistance tests to ensure reliability. The JADA diagnostic group has been conducting gamma ray irradiation experiments on diagnostic components at QST since 2018. The MFC is a neutron diagnostic system that uses uranium fission chambers, the mineral-insulated cables of which were evaluated for corrosion resistance. In-situ observations of the MFC preamplifier have been launched. The PoPola provides the plasma current profile by detecting the polarizations of far-infrared laser beams at their inlets and outlets. Irradiation tests confirmed the durability of PoPola piezo actuators. The ETS is a laser-aided diagnostic to measure electron temperature and density in plasmas from scattered spectra. Laser-induced damages to the optical elements caused by irradiation were investigated. The DIM is a spectroscopic system having a wavelength range of 200 nm to 1000 nm. The effects of irradiation on optical devices, metal mirrors, and radiation-resistant optical fibers were investigated. The IRTh is an infrared thermography system to observe the surface temperature of the divertor. The optical elements and electrical devices of the IRTh have undergone irradiation experiments. The progress of the gamma ray irradiation experiments on the ITER diagnostic systems from JADA are reported.

Physical mechanism of material flow and temperature distribution in keyhole plasma arc welding at initial unstable stage

The initial unstable stage associated with keyhole plasma arc welding affects the stability and quality heavily, especially in the non-vertical welding position, which is difficult to control and restricts the process development and application. This work clarifies the temperature distribution and flow behavior of the process from the digging keyhole stage to the keyhole stable movement stage via an infrared thermography system and high-speed camera system. The experimental results showed that the molten metal on the rear side of the keyhole gradually accumulates and solidifies on the exit side and rear wall of the keyhole. When enough molten metal accumulates on the keyhole rear sidewall, it closes under the action of surface tension. The angle (86°–90°) of the keyhole rear sidewall formation can be used to determine whether the keyhole rear side is closed and reached the keyhole stable movement stage. Simultaneously, the influence of the shifting direction of gravity on the temperature distribution, flow behavior, and solidification morphology of the keyhole weld pool was investigated, which further revealed the initial unstable stage of the welding process. In the flat position, at this stage, the high-temperature area within the keyhole rear sidewall surface gradually accumulates close to the exit side of the weld pool. More molten metal flows to the keyhole exit side by gravity and shear forces, which causes a separation area on the keyhole rear side that is nearer to the exit side of the weld pool. This makes it harder to close the keyhole wall when it is in a flat position during the initial unstable stage. Furthermore, the temperature distribution and flow behavior of the keyhole rear side can be used as another factor to characterize the flow state of the weld pool in all positions and stages of welding.

An iterative algorithm to improve infrared thermographic systems’ accuracy in temperature field measurement of aluminum alloys

Accurate real-time measurement of temperature is vital for ensuring successful production of aluminum alloy parts. As an excellent approach to real-time measurement of aluminum alloys’ temperature field, infrared thermal imaging systems enable non-contact, fast-response measurement. However, the emissivity of aluminum alloys varies by temperature, making accurate measurements by infrared thermographic systems unavailable. For this reason, an emissivity iterative algorithm is proposed in this paper. The emissivity-temperature curves of aluminum alloys are obtained and used for the correction of the temperature field. The algorithm helps infrared thermal imaging systems reduce their dependency on emissivity and thus realizes a precise temperature field measurement for aluminum alloy. To validate this model, we conduct experiments to measure the temperature field of uniformly heated aluminum alloys, and of friction stir welding. Results of the experiments show this model can effectively improve the accuracy of infrared thermographic systems for measuring the temperature field of aluminum alloys.

Redundant Fault Diagnosis for Photovoltaic Systems Based on an IRT Low-Cost Sensor.

In large solar farms, supervision is an exhaustive task, often carried out manually by field technicians. Over time, automated or semi-automated fault detection and prevention methods in large photovoltaic plants are becoming increasingly common. The same does not apply when talking about small or medium-sized installations, where the cost of supervision at such level would mean total economic infeasibility. Although there are prevention protocols by suppliers, periodic inspections of the facilities by technicians do not ensure that faults such as the appearance of hot-spots are detected in time. That is why, nowadays, the only way of continuous supervision of a small or medium installation is often carried out by unqualified people and in a purely visual way. In this work, the development of a low-cost system prototype is proposed for the supervision of a medium or small photovoltaic installation based on the acquisition and treatment of thermographic images, with the aim of investigating the feasibility of an actual implementation. The work focuses on the system's ability to detect hot-spots in supervised panels and successfully report detected faults. To achieve this goal, a low-cost thermal imaging camera is used for development, applying common image processing techniques, operating with OpenCV and MATLAB R2021b libraries. In this way, it is possible to demonstrate that it is achievable to successfully detect the hottest points of a photovoltaic (PV) installation with a much cheaper camera than the cameras used in today's thermographic inspections, opening up the possibilities of creating a fully developed low-cost thermographic surveillance system.

Defect Detection of Electrical Insulating Materials Using Optically Excited Transient Thermography and Deep Autoencoder

This article presents an automatic and unsupervised internal damage detection technique for electrical insulating materials using optically excited transient thermography and a deep autoencoder (DAE). For this purpose, an optically excited thermography system is built, and the thermal images of the specimen surface during the cooling period are collected for the training of the DAE model. The reconstruction error of the DAE model is used as a feature to generate the feature image. The final binary detection image is obtained by applying adaptive threshold image segmentation. To avoid unwanted errors, small connected components and isolated pixels are removed as they may be falsely considered damages in the feature image. To improve the detection accuracy and reliability, the architecture and hyperparameters of the DAE network are optimized. The featured image and segmented image obtained using the DAE are compared with those obtained using three other traditional methods [manual time-domain image selection, frequency-domain feature analysis, and principal component analysis (PCA)]. Based on the defined evaluation metrics, the proposed DAE framework exhibits the best visual effects and the highest defect detection accuracy. The test results also show that this method is effective in detecting real composite insulators with air-gap defects under different detection interferences.

Automatic Detection of CFRP Subsurface Defects via Thermal Signals in Long Pulse and Lock-In Thermography

Thermography is widely used to detect delamination defects in carbon fiber reinforced plastics (CFRP). This paper proposes a model to detect defects automatically by extracting the thermal signal characteristics of CFRP materials. An optically excited thermography system is constructed for pulsed and lock-in thermography experiments to compare thermal signal data sets in different excitation modes. A multi-task joint loss function is defined to train the model for defect detection and depth prediction. The effects of different attention modules (AM) are analyzed to improve the model performance. By comparing the effects of traditional thermography processing methods and methods based on Convolutional Neural Network (CNN), it is found that the proposed model can detect defects with minimum aspect ratio (ratio of short side to depth) of 2.5, and the relative error percentage in depth prediction is below 10%.

A Flexible Wearable Thermography System Based on Bioheat Microsensors Network for Early Breast Cancer Detection: IoT Technology

Many women diagnosed by traditional screening methods, such as palpation, mammography, and MRI, do not discover their cancer until it is relatively advanced. This makes treatment more difficult and reduces the chance of a cure. To deal with this issue, we have developed a noninvasive embedded thermography system that allows for an early detection of breast cancer. Indeed, the surface temperature distribution of the breast, which we will call the thermal image, can be used as a preventive indicator of the subsequent development of a cancerous tumor. This is due to the metabolic activity of the immune system, which induces, in the presence of cancer cells, a local increase of temperature even before the tumor tissue is differentiated and detectable by conventional imaging systems. The proposed system is designed as a network of bioheat microsensors applied to the breast, to measure periodically the temperature gradients on the surface. All the bioheat microsensors are addressed by a microcontroller via the I2C protocol. To calibrate and evaluate the proposed system, we have proposed an experimental model of the breast, inside which we have placed Joule effect heating elements.

The wide-angle infrared diagnostic for the first wall monitoring of the WEST tokamak

A tangential infrared thermography system is installed in the WEST tokamak to observe the thermal scene of the first wall and the divertor components through a wide-angle tangential view. The goal is to provide and monitor the heat load deposition on the plasma facing components. About one-sixth of the chamber is observed, including sectors of the baffle, the lower and upper divertors, one inner bumper, vertical displacement event (VDE) protections, one ICRH antenna, and other parts of the wall. It is used for real time machine protection by monitoring temperature thresholds in delimited region of interest, and for analysis of normal or specific heat load events during operation such as VDE, ELM, disruption or runaways. This wide-angle view uses one aspherical and one on-axis plane mirrors, a sapphire window and three lenses for the objective of the camera. The optical line is optimized for two wavelengths 1.7 and 4 µm. The field of view is 60° on a 512×640 pixels Focal Plane Array. The endoscope is fully actively cooled. The thermal scene is complex to interpret given the fully metallic and radiative environment and the uncertainties on the emissivity which is angular-dependent and changes with the surface properties. This involves significant inaccuracy on the recovery of the real temperature. In this context, an interpretation by modeling approach is better suited, based on ray-tracing simulations taking into account the optical properties of materials. For instance, this allowed discriminating reflections patterns from real thermal events in the wide-angle view. A description of the wide-angle infrared diagnostic and its performances is presented as well as experimental measurements obtained in the WEST Tokamak.

Scanning Induction Thermography for Bearing Ring Under AC-DC Composite Magnetization

Induction thermography is a promising nondestructive testing technique with the advantages of high efficiency, lift-off tolerance, and defect imaging. To fulfill scanning detection and quantify the defect in bearing rings, this paper proposes scanning eddy current thermography under AC-DC composite magnetization. With DC magnetization, the defect will cause permeability disturbance in the bearing ring surface. Under high-frequency AC magnetization, disturbed permeability will generate a non-uniform thermal response captured by the infrared camera. To investigate the detection principle, a multi-physics coupling simulation model for permeability and thermal distribution in the scanning process is built, involving DC-AC composite magnetization, nonlinear ferromagnetic material, heat generation, heat conduction, and scanning movement. Then, a thermal data post-processing method for scanning imaging and crack quantification is proposed. Finally, the scanning induction thermography system for bearing rings is designed and developed. The experimental results show that the proposed scanning method can quantify bearing ring cracks with depths up to 2.0 mm.

Active 3-D Thermography Based on Feature-Free Registration of Thermogram Sequence and 3-D Shape Via a Single Thermal Camera

Active three-dimensional(3-D) thermography combines 3-D shape and active thermography. Thus, it enables the provision of the intuitive thermographic inspection results for composite parts with a complex geometry. However, conventional 3-D thermography acquires thermographic information and 3-D shape through at least two independent sensors and requires complex cross-modal image registration algorithm based on the keypoint detection and matching. In this article, an active 3-D thermography system is proposed using only one thermal camera for moving objects. This system does not require an independent 3-D sensor while the thermal camera acts as the 3-D sensor. Nature behind that is that a mathematical model is proposed to unify the line scanning thermography and laser triangulation in the dynamic scanning process, taking a line laser as both heat excitation for active thermography and spatial coding for 3-D reconstruction. Furthermore, the model enables the feature-free registration of thermogram sequence and 3-D shape, so that the registration is fast and robust without keypoint features. The experiments on standard height specimens, 3-D printing glass fiber composites, and carbon fiber intake tube have shown the error is calibrated within 0.25 mm in the range of 1 to 150 mm and evidenced the capability for subsurface defects detection. The ease and robustness of the proposed active 3-D thermography have a bright future for 3-D measurement, defects detection, and quality control in the production line.

Thermography as a Method for Bedside Monitoring of Infantile Hemangiomas.

Infantile hemangiomas occur in 3 to 10% of infants. To predict the clinical course and counsel on treatment, it is crucial to accurately determine the hemangiomas' extension, volume, and location. However, this can represent a challenge because hemangiomas may present irregular patterns or be covered by hair, or their depth may be difficult to estimate. Diagnosis is commonly made by clinical inspection and palpation, with physicians basing their diagnoses on visual characteristics such as area, texture, and color. Doppler ultrasonography or magnetic resonance imaging are normally used to estimate depth or to confirm difficult assessments. This paper presents an alternative diagnosis tool-thermography-as a useful, immediate means of carrying out accurate hemangioma examinations. We conducted a study analyzing infantile hemangiomas with a custom thermographic system. In the first phase of the study, 55 hemangiomas of previously diagnosed patients were analyzed with a thermal camera over several sessions. An average temperature variation before and after treatment of -0.19 °C was measured. In the second phase, we selected nine patients and assessed their evolution over nine months by analyzing their thermographic images and implementing dedicated image processing algorithms. In all cases, we found that the thermal image analysis concurred with the independent diagnoses of two dermatologists. We concluded that a higher temperature inside the tumor in the follow-up was indicative of an undesirable evolution.

Ice accretion thickness prediction using flash infrared thermal imaging and BP neural networks

The present study investigated ice accretion thickness under non-incoming flow icing conditions on the ground using an infrared thermography system that converts infrared radiation temperature. Two back propagation (BP) neural network models were developed to measure ice thickness. Both theoretical model and polynomials were employed to fit the icing surface temperature elevation sequence to extract the pixel-level temperature attenuation characteristics, which were served as the input to the BP neural networks. The prediction method of ice thickness by the BP neural network was analysed from three perspectives of sensitivity, dimension, and precision. In addition, K-nearest neighbour (KNN) and support vector regression (SVR) algorithms were compared with BP neural network. In terms of prediction effect, the BP neural network performed the best. The verification of the BP neural network based on the characteristics of the theoretical model proved that the method can effectively predict the thickness of ice accretion, and its prediction error does not exceed 10%.

System for acquisition and transmission of thermal images to monitor equipment of an electrical substation

Thermographic monitoring systems are achieving satisfactory results in identifying points with anomalous temperature, preventing faults to occur. In the development of a methodology for automatic analysis of thermal images, an automated system for data acquisition and transmission is necessary. This article aims to compare the different ways to acquire images from a thermal camera FLIR® A700: Atlas SDK, web interface and Rest API, among which the latter stands out because of its simplicity and easy implementation. The article also describes the developed software for automated capture of thermal images and the communication system developed to transmit these images.

A quantitative study on the thermomechanical coupling effect of elasticity and plasticity of polymethyl methacrylate

Quantitative study on the elastic and plastic thermomechanical coupling effect of solid materials has important theoretical significance for monitoring the deformation state and stability evaluation of engineering components. In this study, the sample is made of polymethyl methacrylate (PMMA), and uniaxial compression experiments are carried out. The sample experiences the elastic state and then the plastic state until the failure of the sample. The thermoelastic effect and thermoplastic effect in the deformation process of PMMA materials are monitored by infrared thermography and digital speckle system (DIC). That is, the relationship between the reversible elastic temperature change ΔTe and average stress change Δσm, and the relationship between the irreversible plastic temperature rise ΔTp and the dissipated energy ΔUp during the failure deformation process. The results show that when the sample is in the elastic regime, there is only elastic temperature change ΔTe inside the sample. When the sample enters the plastic deformation regime, the total temperature change ΔT includes elastic temperature change ΔTe and plastic temperature change ΔTp, and the temperature change has an obvious memory effect on the previous maximum load. When the previous maximum load exceeded, ΔTp increases rapidly. When the load P is removed, ΔTe disappears, and ΔTp remains. Combined with the theory of thermodynamics and solid mechanics, starting from the 3D stress state, the approximate linear incremental relationship between Te and σm, and the accurate exponential total quantity relationship are derived. The incremental relationship and the full relationship combined with thermodynamic theory and the energy conservation principle, the relationship between the overall plastic temperature rise ΔTp and local plastic temperature rise ΔTpmax of the sample and the energy dissipation value ΔUp experienced by the sample and the local dissipation specific energy Δup is obtained. The theoretical calculation results of ΔTe and ΔTp are in good agreement with the experimental results. The research results can provide a new method for monitoring and identifying the stress and deformation state of engineering components through the temperature field.

Development of inverse methods for infrared thermography in fusion devices

• Infrared quantitative thermography challenging in fully reflective and radiative environment. • Development of inverse processing using infrared synthetic diagnostics to retrieve the real surface temperature in tokamak. • Comparison of inverse methods based on a gradient minimisation and machine learning techniques. Infrared (IR) thermography system is a key diagnostic in fusion devices to monitor the Plasma Facing Components. Nevertheless, both qualitative and quantitative analysis (i.e. hot spot detection and surface temperature measurement) are challenging due to the presence of disturbance phenomena like variable emissivity and multiple reflections in fully metallic environment. Through the comparison with the experimental IR measurements, simulation is an essential tool for anticipating, quantifying and analysing the effects of the various errors involved in the interpretation of IR images. This paper goes a step further for achieving IR quantitative thermography in developing inverse methods to retrieve the real surface temperature, by taking into account variable emissivity and filtering reflections. Two approaches are studied: (1) using gradients methods through a reduced photonic model (2) using machine learning techniques based on simulated dataset. Applied on WEST-like tokamak numerical prototype, the temperatures are estimated, with these two approaches, with an accuracy better than 6%, which is a clear improvement compared to usual methods (i.e. assuming blackbody object).

Dependence of scrape-off layer profiles and turbulence on gas fuelling in high density H-mode regimes in TCV

A set of high density, highly shaped H-mode discharges has been performed in the TCV tokamak with the aim of assessing the effects of increasing divertor neutral recycling on the properties of upstream inter-ELM scrape-off layer (SOL) profiles and transport. An increase of divertor neutral pressure has been correlated with the evolution of separatrix properties and turbulence level. The latter has been quantified by means of the α t parameter introduced in (Eich 2020 Nucl. Fusion 60 056016), describing the contribution of resistive-interchange turbulence in the SOL relative to drift wave transport. The analysis reveals a general broadening of the upstream SOL profiles as α t increases, with the SOL power width measured by the vertical IR thermography system increasing significantly. In a similar way, the upstream density profile widens in the near SOL, whereas in the far SOL a density shoulder is observed to progressively form and increase in amplitude. This behaviour is associated with an enhancement of far SOL turbulent transport in the form of blob-filaments travelling radially faster across the far SOL and becoming bigger at higher α t. The detected filaments, evaluated from the fast reciprocating probe at the outer midplane, are determined to mostly belong to the resistive ballooning and resistive X-point regimes.