Thermal Imaging System Research Articles

Unmanned Aerial Vehicle with Thermal Imaging for Automating Water Status in Vineyard

Thermal imaging is utilized as a technique in agricultural crop water management due to its efficiency in estimating canopy surface temperature and the ability to predict crop water levels. Thermal imaging was considered as a beneficial integration in Unmanned Aerial Vehicle (UAV) for agricultural and civil engineering purposes with the reduced weight of thermal imaging systems and increased resolution. When implemented on-site, this technique was able to address a number of difficulties, including estimation of water in the plant in farms or fields, while considering officially induced variability or naturally existing water level. The proposed effort aims to determine the amount of water content in a vineyard using the high-resolution thermal imaging. This research work has developed an unmanned aerial vehicle (UAV) that is particularly intended to display high-resolution images. This approach will be able to generate crop water stress index (CWSI) by utilizing a thermal imaging system on a clear-sky day. The measured values were compared to the estimated stomatal conductance (sg) and stem water (s) potential along the Vineyard at the same time. To evaluate the performance of the proposed work, special modelling approach was used to identify the pattern of variation in water level. Based on the observation, it was concluded that both ‘sg’ and ‘s’ value have correlated well with the CWSI value by indicating a great potential to monitor instantaneous changes in water level. However, based on seasonal changes in water status, it was discovered that the recorded thermal images did not correspond to seasonal variations in water status.

Non-contact breathing monitoring by integrating RGB and thermal imaging via RGB-thermal image registration

Altered breathing rate is an important sign of disease status. Currently used machine-based monitoring of the breathing rate includes contact with the body, which may result in pain and discomfort. In this paper, a non-contact breathing monitoring technique is proposed by integrating RGB and thermal imaging systems with RGB-thermal image registration. This method provides a linear mapping for automated selection of the region of interest (ROI) followed by tracking to extract the breathing rate. To evaluate the efficacy of the proposed approach and its robustness against motion, talking, varying breathing rate or rhythm, and high ambient temperature, this study was conducted in three phases. Validation of the proposed approach demonstrated a strong agreement with the reference method of breathing rate monitoring using a respiration belt. During normal breathing, the mean absolute error (MAE) reached 0.11 bpm (breaths per minute). While in more challenging conditions, defined by three phases, the MAE reached 1.46, 2.08, and 1.69 bpm, respectively. In short, the proposed method performance is a promising alternative to a contact-based method due to its strong agreement and might be useful in diverse applications such as sport studies, rehabilitation centres, quarantine centres, and in hospital or airport screening during the COVID 19 pandemic.

Low-temperature test objects for alignment of thermal imaging systems

Structurally simple low-temperature dashed test objects (miras) with elements at temperatures lower than ambient are presented. These devices are based on thermoelectric elements (Peltier modules) with interchangeable thermal-insulating substrates mounted on them. The substrates have rectangular openings and heat-emitting conducting layers applied to the surface. Experimental thermograms of the models of test-objects are presented. The proposed devices are designed to align thermal imaging systems. They enhance the possibilities of investigating such systems and can be applied either separately or within infrared collimators.

Research on Performance Evaluation and Optimization Theory for Thermal Microscope Imaging Systems

Infrared imaging theory is an important theoretical basis for the design of infrared imaging systems, but there is no research on infrared imaging theory for designing thermal microscope imaging systems. Therefore, we studied the performance evaluation and optimization theory of thermal microscope imaging systems. In this paper, we analyzed the difference in spectral radiant flux between thermal microscope imaging and telephoto thermal imaging. The expression of signal-to-noise ratio of the output image of the thermal microscope imaging systems was derived, based on the analysis of the characteristics of thermal microscope imaging. We studied the performance evaluation model of thermal microscope imaging systems based on the minimum resolvable temperature difference and the minimum detectable temperature difference. Simulation and analysis of different detectors (ideal photon detector and ideal thermal detector) were also carried out. Finally, based on the conclusion of theoretical research, we carried out a system design and image acquisition experiment. The results show that the theoretical study of thermal microscope imaging systems in this paper can provide reference for the performance evaluation and optimization of thermal microscope imaging systems.

In situ photo-thermal conversion nanofiber membrane consisting of hydrophilic PAN layer and hydrophobic PVDF-ATO layer for improving solar-thermal membrane distillation

Solar thermal membrane distillation is a promising technology for low-cost desalination and water purification. A novel photo-thermal conversion membrane composited by polyacrylonitrile (PAN) nanofiber layer and polyvinylidene fluoride (PVDF) with antimony tin oxide (ATO) as solar-thermal nanoparticles (PVDF-ATO/PAN nanofiber membrane) was fabricated by sequent electrospinning techniques. The dual-layer membrane with hydrophilic PAN and hydrophobic PVDF-ATO was examined by microscopic evaluation and contact angle measurement. In situ temperature increase on membrane superficial layer (PVDF-ATO) driven by solar light illumination was confirmed by thermal imaging system. PAN layer provides water transport channels for facilitating water flow of highly efficient membrane distillation and avoids the salting assembly during the vigorous evaporation. With the help of hydrophilic PAN layer, our PVDF-ATO/PAN nanofiber membrane can fulfill highly effective localized heating transfer with an evaporate rate of 0.93 kg m−2 h−1, showing great potential for low-cost water desalination and scalable water purification.

MS-AFF: a novel semantic segmentation approach for buried object based on multi-scale attentional feature fusion

Infrared technology is widely used in buried object detection since it can capture the heat radiated outward from the target objects. Compared to the visible images, infrared images present poor resolution, low contrast, and fuzzy visual effect, making it challenging to detect the target objects, specifically in complex backgrounds. In recent years, deep learning-based methods have made significant improvements in detection tasks. However, infrared images of buried objects are difficult to obtain. Less training samples, worse performance of deep-learning based detection. We raise a multi-scale attentional feature fusion module for infrared image semantic segmentation to solve this problem. Precisely, we integrate a series of feature maps from different levels by an atrous spatial pyramid structure. In this way, the model can obtain rich representation ability on the infrared images. Besides, a global spatial information attention module is employed to let the model focus on the target region and reduce disturbance in infrared images’ background. In addition, we propose an infrared segmentation dataset based on the infrared thermal imaging system. Finally, we use state-of-the-art object detection methods to train the buried object dataset and compare them with our proposed method. Extensive experiments on infrared segmentation dataset demonstrate the superiority of our method.

Effect of transverse trench on film cooling performances of typical fan-shaped film-holes at concave and convex walls

By means of a time-resolved infrared thermal imaging system, the effect of transverse trench on the film cooling performances of a fan-shaped film-hole at typical concave and convex walls was discussed deeply, from a combined view of the time-averaged parameter evaluation and cooling unsteadiness level analysis. Harmful cooling unsteadiness with high level can be estimated by large standard deviation (SD) of transient film effectiveness, which is generated by the intensified temporal evolutions of vortex-footprints at wall. Comparisons of the time-averaged experimental results revealed the design of trench at curved walls can effectively improve the film effectiveness, completely different from the phenomenon of previous flat-plate studies. The increments in area-averaged effectiveness are nearly non-sensitive to cooling air flowrate, which can reach 27% and 16% at the concave and convex walls, respectively. Meanwhile, the trench can cause the relatively small aerodynamic loss at curved walls. Analysis of cooling unsteadiness can provide the new horizon to estimate the benefits of film cooling design. Thus, the transverse trench structure is strongly suggested at convex wall, due to the reduced level of cooling unsteadiness; however, the improved level of cooling unsteadiness can impede the direct application of transverse trench at concave wall. Steady numerical simulations were also conducted to provide the detailed knowledge of flow mechanisms. The variations of intensities of vortex-system result in the different jet reattachments downstream of trench caused by wall curvature. The difference of cooling unsteadiness levels is mainly determined by the turbulence quality of impingement to trench-edge. An additional information from the present study was introduction of trench can obviously change the trends in film effectiveness and SD-contour with wall curvature. The variations of turbulence dissipation cause a break of the wall curvature effect on film effectiveness at blowing ratio (BR) of 1.5, indicting the highest effectiveness is acquired by the convex model under small BRs whereas by the concave model under large BRs.

Design and development of smart monitoring module for detection of virus

The big issue encountered these days across the world is the spreading of virus. Early detection of the virus prevents it from spreading. The paper is presenting a method of an innovative real-time early detection of virus and monitoring system using smart wrist band linked with virus detection (VD) APP which is integrated with thermal imaging system, positioning system, optical system, and liquid controller. The smart wrist band detects high body temperature of the person who is wearing, position among the two people and displays the data on the APP which is further linked to Police through GPS. The proposed method has also provision to check the temperature of a person who is in and around to him/her who is wearing smart band and if the temperature is high than it will send a notification through GPS and using optical system it will take image of the concerned person which is further sent to the concerned authorities through APP. The proposed method also detects the person whether he is wearing the mask or not. The diagnosis of the screening process is less time consuming and less human interactions that might cause the spreading of the virus.

Dual Modal Imaging-Guided Drug Delivery System for Combined Chemo-Photothermal Melanoma Therapy.

PurposeMalignant melanoma is one of the most devastating types of cancer with rapid relapse and low survival rate. Novel strategies for melanoma treatment are currently needed to enhance therapeutic efficiency for this disease. In this study, we fabricated a multifunctional drug delivery system that incorporates dacarbazine (DTIC) and indocyanine green (ICG) into manganese-doped mesoporous silica nanoparticles (MSN(Mn)) coupled with magnetic resonance imaging (MRI) and photothermal imaging (PI), for achieving the superior antitumor effect of combined chemo-photothermal therapy.Materials and MethodsMSN(Mn) were characterized in terms of size and structural properties, and drug loading and release efficiency MSN(Mn)-ICG/DTIC were analyzed by UV spectra. Photothermal imaging effect and MR imaging effect of MSN(Mn)-ICG/DTIC were detected by thermal imaging system and 3.0 T MRI scanner, respectively. Then, the combined chemo-phototherapy was verified in vitro and in vivo by morphological evaluation, ultrasonic and pathological evaluation.ResultsThe as-synthesized MSN(Mn) were characterized as mesoporous spherical nanoparticles with 125.57±5.96 nm. MSN(Mn)-ICG/DTIC have the function of drug loading-release which loading ratio of ICG and DTIC could reach to 34.25±2.20% and 50.00±3.24%, and 32.68±2.10% of DTIC was released, respectively. Manganese doping content could reach up to 65.09±2.55 wt%, providing excellent imaging capability in vivo which the corresponding relaxation efficiency was 14.33 mM−1s−1. And outstanding photothermal heating ability and stability highlighted the potential biomedical applicability of MSN(Mn)-ICG/DTIC to kill cancer cells. Experiments by A375 melanoma cells and tumor-bearing mice demonstrated that the compound MSN(Mn)-ICG/DTIC have excellent biocompatibility and our combined therapy platform delivered a superior antitumor effect compared to standalone treatment in vivo and in vitro.ConclusionOur findings demonstrate that composite MSN(Mn)-ICG/DTIC could serve as a multifunctional platform to achieve a highly effective chemo-photothermal combined therapy for melanoma treatment.

Algorithm for Automated Foot Detection in Thermal and Optical Images for Temperature Asymmetry Analysis

Infrared thermography has been proven to be an effective non-invasive method in diabetic foot ulcer prevention, yet current image processing algorithms are inaccurate and impractical for clinical work. The aim of this study was to investigate the accuracy of our automated algorithm for feet outline detection and localization of potential inflammation regions in thermal images. Optical and thermal images were captured by a Flir OnePro camera connected with an Apple iPad Air tablet. Both thermal and optical images were merged into an edge image and used for the estimation of foot template transformations during the localization process. According to the feet template transformations, temperature maps were calculated and compared with each other to detect a set of regions exceeding the defined temperature threshold. Finally, a set of potential inflammation regions were filtered according to the blobs features to obtain the final list of inflammation regions. In this study, 168 thermal images were analyzed. The developed algorithm yielded 95.83% accuracy for foot outline detection and 94.28% accuracy for detection of the inflammation regions. The presented automated algorithm with enhanced detection accuracy can be used for developing a mobile thermal imaging system. Further studies with patients who have diabetes and are at risk of foot ulceration are needed to test the significance of our developed algorithm.

Crystallization and thermal stability effects on tailings glass-ceramics by various heat treating processes

Increasing environmental concerns raise attention on the recycling of mining wastes and smelting of byproducts. As one of the candidate materials, slag glass-ceramics give full play to effective use of tailings resources with excellent performance. In the present research, Bayan Obo tailings are used to produce slag glass-ceramics. However, the effect of the preparation process on the stable behavior and crystallization mechanism of glass-ceramics is still being explored. In this study, different heat treatment processes are used to prepare slag glass-ceramics and its effects on the stability and performance are evaluated through different glass crystallization characteristics. X-ray diffraction (XRD), differential scanning calorimetry (DSC), high-resolution scanning electron microscopy (SEM), Spectral analysis techniques (FT-IR and Raman spectroscopy), and high-temperature thermal imaging system (Tomac) are performed to study and characterize the stable behavior and mechanism of glass-ceramics. Results show that glass-ceramics with heat treatment at 1000 °C exhibit competitive mechanical properties. High crystallization temperature promotes the crystallization of the glass and enhances the growth of crystal grains to optimize the stability and physical properties of the glass-ceramics. In this research, a new process parameter model is provided for process optimization in the industrial production process of glass-ceramics.

Luminescent polyurethane composite with real-time thermal response via visible signal

Visible signals are vital to human communication. Thermal signals are often difficult to observe unless they are in physical contact with the subject or an infrared thermal imaging system is used. In this study, we prepared a luminescent polyurethane composite (LPC), which can intelligently alter its colour and luminescence based on temperature. The LPC is fabricated from rare-earth luminescent materials (Sr2ZnSi2O7: Eu2+, Dy3+ and Y2O2S: Eu3+, Mg2+, Ti4+), a heat-sensitive rose-red TF-R1 thermochromic pigment (TP), polyurethane (PU), and polyester fabric. Microstructure and crystal structure analyses were carried out to determine the basic material properties of the LPC. The reflectivity and K S−1 value under different temperatures indicate that blue and green light were absorbed by LPC at 25 °C and the absorption decreased at 45 °C. This results in the LPC turning white. The emission spectra demonstrate that the quinoid structure of TP blocked the light of Sr2ZnSi2O7: Eu2+, Dy3+. Meanwhile, the lactone structure of TP allowed the light emission of Sr2ZnSi2O7: Eu2+, Dy3+ and Y2O2S: Eu3+, Mg2+, Ti4+. As a result, LPC emits red light at low temperatures and blue light at high temperatures. The advantage of the fabricated LPC is that the output can be easily manipulated into patterns. The uncured PU could form various graphics to cooperate with visible signals. Therefore, the LPC has significant potential as a functional material in smart clothing, flexible electronics, and wearable devices.

Testing and evaluation method for HDR thermal imaging system dynamic range performance

Testing and evaluation method for HDR thermal imaging system dynamic range performance

Design and implementation of infrared thermal imaging system based on SOPC

Design and implementation of infrared thermal imaging system based on SOPC

Application of Zernike moments in computer vision problems for infrared images

The efficiency of using Zernike moments when working with digital images obtained in the infrared region of the spectrum is considered to improve the accuracy and speed of an autonomous thermal imaging system. The theoretical justification of the choice of Zernike moments for solving computer (machine) vision problems and the choice of a suitable threshold binarization method is given. In order to verify the adequacy and expediency of using the chosen method, practical studies were conducted on the use of Zernike methods for distorting various thermal images in shades of gray.

MONITORING THE CONDITION OF VEGETABLES, FRUITS AND PLANTS USING INFRARED THERMOGRAPHYMONITORING THE CONDITION OF VEGETABLES, FRUITS AND PLANTS USING INFRARED THERMOGRAPHY

Determining the quality of fruit and vegetable products and their storage is a topical problem, as evidenced by a significant number of works from near and far abroad. These works present the worldwide experience of using various optical methods for instrumental non-destructive assessment of the maturity and commercial quality of fruit and vegetables. Despite so many scientific works on this topic, the thermographic methods require further research to find out the prospects of using modern thermal imaging systems in the agricultural sector. The paper studies the possibility of using remote-sensing infrared thermography to monitor the state of vegetables, fruit, and plants during their growth and storage. To determine the quality of fruit and vegetable products by random sampling, apples, pears, and pumpkins, with no external (visible) damage, were tested for the presence of microbial infections in them during rotting. In a laboratory environment, the plants were studied after watering to determine the process of hydration through the trunk and leaves and thus assess their condition. The research used a matrix infrared thermograph developed by V.Lashkaryov Institute of Semiconductor Physics of the National Academy of Sciences of Ukraine. The studies have shown that infrared thermography detects internal damage to fruit and vegetables and allows assessing the watering of plants and their condition. As a result of this work, it has been shown that infrared thermography, as a diagnostic method, can be recommended for timely detection of the internal development of microbial infections that lead to spoilage of vegetables and fruit during long-term storage, as well as for monitoring the state of plants during their hydration. It has been shown that infrared thermography can be used to control the quality of fruit and vegetable products before putting them in long-term storage and during it. The method allows timely detection of damage, and is helpful in studying plants in the laboratory and in the field.

Application of thermal imaging for detecting cold air leak location in cold storage

<span>Nowadays Cold storage has been playing an important role in preserving the perishable food products like fruits, vegetables, dairy products, fish, and meat etc. The major problem of cold storage is unwanted energy transmission during the operation. It is necessary to maintain the constant temperature during storing the products. There are different kinds of energy loss happening during the operation. One of the major causes is cold air leaking from the inside of the cold room to outside. It is due to poor insulation and improper maintenance of cold storage. It is very difficult to identify the exact location of the leak by the naked eye. In this research work, the cold storage was inspected with the thermal imaging system. Thermal cameras are highly sensitive to temperature and it can detect the variation of temperature ranging from 0.1°C. The measured temperatures are further converted into a colour based pattern. It is known as thermogram. These colour-based thermal patterns are further processed for identifying energy transmission location. It is done by applying various image processing methods such as histogram equalization, diffusion error, otsu thresholding and morphologic function. These techniques were applied to images of cold storages and exact cold air transmission locations were identified.</span>

Optimizing Impedance Change Measurement During Radiofrequency Ablation Enables More Accurate Characterization of Lesion Formation.

This study sought to determine whether a novel impedance thermal imaging system (ITIS) provides an impedance measurement that is better correlated with lesion dimensions than circuit impedance during radiofrequency (RF) ablation. A 5- to 10-Ω impedance drop is clinically used to corroborate an effective RF ablation lesion. However, the contribution of local tissue heating to circuit impedance change is small and dependent on the local environment of the catheter and placement of the grounding patch. ITIS uses ablation catheter and skin electrodes to perform 4-terminal impedance measurements with separate voltage sensing and current injection electrode pairs. Seven sheep underwent endocardial ventricular irrigated RF ablation at 40W for 60 s. ITIS impedance and circuit impedance were both measured throughout ablation. When the sheep were sacrificed, ablation lesions were cut along their long axis; the depth, width, and surface area of the cut surface were measured. A total of 68 RF ablations were performed, with a median depth of 3.5mm (interquartile range [IQR]: 2.1 to 4.9mm), width of 8.3mm (IQR: 5.7 to 10.8mm), and surface area of 23.8mm2 (IQR: 9.3 to 43.0mm2). ITIS impedance change had good correlation with lesion depth, width, and surface area (R=0.76, R=0.87, and R=0.87, respectively); and superior to circuit impedance for lesion depth, width, and surface area (p=0.0018, p=0.0004, and p=0.0001, respectively). By optimizing the current path and using 4-terminal impedance measurement during RF ablation, the contribution of tissue temperature changes to measured impedance is better standardized to provide a more reliable measure than conventional ablation circuit impedance.

Influence of the reinforcement scheme on mechanical properties of 2d, 3d polymer composites

This work provides the results of complex study of mechanical properties of the composition materials based on carbon fiber 3D-preforms and epoxy binder (carbon fiber A-49 by AKSA + epoxy resin T26 by INUMiT CJSC), as well as the analysis of benefits, merits and demerits from the viewpoint of complex analysis of mechanical properties and structural process stability. The paper presents the values of the main mechanical characteristics for all types of materials in proportions for all types of tests. A comprehensive analysis of the mechanical behavior, patterns of damage accumulation and destruction of composite samples was carried out using additional registration means: the method of recording acoustic emission signals, the method of digital image correlation and an infrared thermal imaging system.

Deep Learning Based Object and Railway Track Recognition Using Train Mounted Thermal Imaging System

An intelligent railways safety system is very essential to avoid the accidents. The motivation behind the problem is the large number of collisions between trains and various obstacles, resulting in reduced safety and high costs. Continuous research is being carried out by distinct researchers to ensure railway safety and to reduce accident rates. In this paper, a novel method is proposed for identifying objects (obstacles) on the railway tracks in front of a moving train using a thermal camera. This approach presents a novel way of detecting the railway tracks as well as a deep network based method to recognize obstacles on the track. A pre-trained network is used that provides the model understanding of real world objects and enables deep learning classifiers for obstacle identification. The validation data is acquired by thermal imaging using night vision IR camera. In this work, the Faster R-CNN is used that efficiently recognize obstacles on the railway tracks. This process can be a great help for railways to reduce accidents and financial burdens. The result shows that the proposed method has good accuracy of approximately 83% which helps to enhance the railway safety.