A Note on Interpreting Tool Temperature Measurements from Thermography

Experimentally validated calculation of the cutting edge temperature during dry milling of Ti6Al4V

Thermography is an efficient way of detecting the thermal problems of the roof as a major part of a building’s energy dissipation. Thermal images have a low spatial resolution, making it a challenge to produce a three-dimensional thermal model using aerial images. This paper proposes a combination of thermal and visible point clouds to generate a higher-resolution thermal point cloud from roofs of buildings. For this purpose, after obtaining the internal orientation parameters through camera calibration, visible and thermal point clouds were generated and then registered to each other using ground control points. The roofs of buildings were then extracted from the visible point cloud in four steps. First ground points were removed using cloth simulation filter (CSF), and then vegetation points were eliminated by applying entropy and red-green-blue vegetation index (RGBVI). Geometric features and a segmentation step were considered to filter roofs from other parts. Finally, by combining visible and thermal point clouds, the generated point had a high spatial resolution along with thermal information. In the achieved results, the thermal camera calibration was performed with an accuracy of 0.31 pixels, and the thermal and visible point clouds were registered with an absolute distance of < 0.3 m. The experimental results showed an accuracy of 18 cm for automated extraction of building roofs and 0.6 pixel for production of a high-resolution thermal point cloud, which was five times the density of the primary thermal point cloud and free from distortions.

This study deals with the influence of tool characteristics on the cutting edge temperature in turning case hardened steel. The cutting test is undertaken with the inserts which have different thermal conductivity and coating layer. The tool edge temperature is measured with a two-color pyrometer. The tool edge temperature increases with the increase in cutting speed. The higher thermal conductivity cutting insert causes lower tool edge temperature. The coating hardly affects the tool edge temperature. The white layer thickness increases with increasing cutting speed reaching a maximum at certain cutting speed and decreases with cutting speed.

Diabetic foot ulceration is the repeated trauma occurring at the region of the feet soles where more pressure is being applied. Ulceration of diabetic foot is very common which frequently lead to the amputation of the foot. Due to ulceration the temperature at these regions increases which is leading to the amputation and results in major wounds at these regions. Conventional methods like Plantar pressure distribution, inspection and palpation do not detect early breakdown in the skin. However temperature distribution measurement can provide information on occurrence of ulceration. Thermal imaging is the technique of determining the temperature distribution measurements on the surface of the skin from the infrared radiation emitted from the surface of the body. These radiations are acquired by the thermal camera and are converted to thermal images. Recent studies confirm that thermal imaging is helpful in the earlier detection of ulceration. The currently available thermography processing techniques are limited to for only general applications. The identification of region of interest with specific anatomic shapes is not possible with these applications. In this proposed work it is aimed to implement and compare two image segmentation techniques for the segmentation of thermal foot images. Also comparison of the two foot sole is done, hence with the help of asymmetry trying to identify ulceration in the subjects at the early stages.

UAV thermal infrared remote sensing technology, with its high flexibility and high temporal and spatial resolution, is crucial for understanding surface microthermal environments. Despite DJI Drones’ industry-leading position, the JPG format of their thermal images limits direct image stitching and further analysis, hindering their broad application. To address this, a format conversion system, ThermoSwitcher, was developed for DJI thermal JPG images, and this system was applied to surface microthermal environment analysis, taking two regions with various local zones in Nanjing as the research area. The results showed that ThermoSwitcher can quickly and losslessly convert thermal JPG images to the Geotiff format, which is further convenient for producing image mosaics and for local temperature extraction. The results also indicated significant heterogeneity in the study area’s temperature distribution, with high temperatures concentrated on sunlit artificial surfaces, and low temperatures corresponding to building shadows, dense vegetation, and water areas. The temperature distribution and change rates in different local zones were significantly influenced by surface cover type, material thermal properties, vegetation coverage, and building layout. Higher temperature change rates were observed in high-rise building and subway station areas, while lower rates were noted in water and vegetation-covered areas. Additionally, comparing the temperature distribution before and after image stitching revealed that the stitching process affected the temperature uniformity to some extent. The described format conversion system significantly enhances preprocessing efficiency, promoting advancements in drone remote sensing and refined surface microthermal environment research.

Finish turning of hardened die tool steel offers an economical alternative to grinding process. This study investigated the effects of machining parameters including workpiece hardness in a range of 45–55 HRC on cutting forces (F c & F t ), surface roughness (R a ) and cutting edge temperature (T) in finish turning of AISIH13 die tool steel with CBN inserts. Workpiece material AISIH13 has been selected on the basis of its wide applications in die making industries in the range of hardness 45–60 HRC. A central composite design has been used for the design of experimentation, and by using response surface methodology, a mathematical model has been developed. This study reported that the cutting forces are primarily influenced by the hardness of workpiece material. The work material hardness, feed rate and depth of cut are also statistically significant on cutting forces. Also, cutting forces increases, with the increase in workpiece hardness, feed and depth of cut, whereas the cutting speed has least impact on cutting forces. In fact, increase in hardness of work material resulted in better surface roughness as well as increase in tool tip temperature. Furthermore, optimum parameters are obtained through multi-response optimization technique using desirability function approach. The novelty aspect of the present study is that it contributes to practical industrial application of finish turning for the die and mold makers to select the optimum cutting conditions in a range of hardness of 45–55 HRC.

Cutting Edge Temperature and Drill Wear in Dry and Minimum Quantity Lubrication Environmentally-Friendly Drilling of the Titanium Alloy

A finite element model (FEM), which is able to predict the cutting interactions between the tool and the workpiece (cutting forces and cutting edge temperature) for a typical aeronautical engine Nickel-alloy Inconel 718, has been used to perform a reduced number of FEM calculations indicated by a DOE, in order to evaluate the design space for process parameters.These well-distributed results can be subsequently used to create and evaluate the quality in terms of correct response behaviour for the metamodels created through different approximation techniques (polynomial and neural network).The metamodels based on the best methodology (in terms of effectiveness of process behaviour prediction) have been used to optimize, through Adaptive Simulated Annealing (ASA) algorithms, the process parameters defined in a CAM part program block.The aim of the authors is to modify the Part Program operation parameters according to the constraints arising from the physical nature of the cutting process obtained by FEA.

Introduction High temperature gas sensors play an important role in monitoring or controlling energy conversion processes. Sensors containing functional materials often need to be heated to a certain operating temperature to achieve functionality. This can be realized using planar thick-film heaters, which are screen-printed on the sensor substrate. When sensors are installed in the exhaust gas flow in order to achieve a fast response behavior, high volume flow has cooling effects on the sensor and leads to an inhomogeneous temperature distribution. This might cause a changed sensor function and cross-sensitivities [1]. For this reason, protective caps are used to reduce the flow influence on the temperature distribution with sufficient response time [2]. Resulting temperature distribution can be simulated using FEM models but cannot be verified directly inside protective caps [3, 4]. The present work solves this uncertainty in two ways to directly measure the temperature homogeneity within a cap. Methods and Setup Sensors are built up on alumina substrates (Figure 1a). On the reverse side, a meander-shaped platinum structure acts as heating element. Two methods are used to determine the temperature distribution on the front side.Firstly, the temperature distribution is recorded by an IR camera (Figure 1c). For optically access, an IR-transparent glass replaces one part of the cap. The requirements for this glass are the transmission of the IR radiation (here attention must be paid to the appropriate wavelength of the camera) and a certain temperature resistance, since the cap and the glass are also heated by the heat radiation of the sensor.Secondly, the temperature distribution is directly measured by means of thermocouples (Figure 1b). Instead of a sensor structure, a matrix of planar screen-printed thermocouples (Figure 1d) is applied onto the front side of the transducer. For this purpose, Pt and Au feedlines are arranged so that five different measuring points are realized at the sensor tip, i.e., that area where a gas sensitive layer would be located. Temperature values are derived from the measured thermvoltage on basis of Seebeck coefficients for Pt/Au given in the literature. Results and Discussion In order to verify the function of the printed thermocouples, the sensor temperature was increased to 600 °C by means of the heater on the reverse side. The heat distribution was recorded by the thermocouples without the protective cap. Thermal images were taken simultaneously with the IR camera. The measured temperature of the thermocouples corresponds well to the thermal images.Afterwards the sensor was placed inside a protective cap containing the described IR-permeable glass window. After increasing the sensor temperature to 600 °C, thermal images of the sensor tip could be taken again. The transmission coefficient of the glass is required for this purpose. To check the accuracy of the transmission coefficient, the temperatures of the thermocouples were recorded simultaneously. The temperature measured by the IR camera again corresponds to the thermocouples values. Thus, the application of this method was also checked and confirmed.Both methods were used to investigate the influence of a protective cap on the temperature distribution on the front side of the sensor at 600 °C operating temperature. Figure 1e) and f) show the temperature distribution of a sensor in a horizontal mounting position recorded by an IR camera (temperature gradients in general come from the individual heater structure and several heat losses, especially heat flow along the substrate material). Figure 1e) shows the measurement without a protection cap. The thermocouple measurement shows a temperature gradient of 6.78 °C/mm between point 1 and 2. The temperature gradient derived from the thermal image is 5.88 °C/mm. Both data (thermocouple and thermal image) agree very well. Then the same measurement was carried out with a protective cap (Figure 1f). The temperature gradient, measured with the thermocouples, is 4.97 °C/mm. The thermal image shows a value of 4.43 °C/mm. The protective cap thus has a positive influence on the temperature homogeneity of a sensor even without a flow. Outlook In the next steps, the temperature distribution in an exhaust flow is investigated by means of the thermocouples. Variations in sensor orientation or mounting positions is possible. Here as well it is possible to investigate the influence of a protection cap. A high temperature setup might be realized by use of screen-printed Pt/PtRh thermopiles [5].

Focus on Analytical Instruments

Automatic analysis of the trunk thermal images from healthy subjects and patients with faulty posture

Thermography captures the temperature distribution of the human skin and is employed in various medical applications. Often it is useful to cross-reference the resulting thermograms with visual images of the patient, either to see which part of the anatomy is affected by a certain disease or to judge the efficacy of the treatment. An attractive approach to provide this information is to overlay the two image types and show a composite image to the clinician. Producing such an overlay however is a non-trivial task due to differences in image capturing conditions of the two modalities. In this paper we introduce an approach that produces accurate overlays of thermal and visual medical images. First unnecessary background information of the visual part are removed by an image segmentation step based on skin detection. The thermal image is then aligned through an intensity based image registration technique. Experimental results based on an set of visual-thermal image pairs demonstrate the effectiveness of the proposed approach

In this article an algorithm for the analysis of raw thermal infrared images is proposed. The images are obtained by using the nondestructive evaluation method of the laser-spot thermography and aim at detecting the presence of surface defects. A laser is used to scan a test specimen through the generation of single pulses. The temperature distribution produced by this thermoelastic source is measured by an infrared camera and processed with a two-stage algorithm. In the first stage, simple mathematical and statistical parameters are used to flag the presence of damage. Then, once damage is detected, the thermal image's first and second spatial derivative and two spatial filters are computed to enhance contrast, and to locate and size the defect. Some of the advantages of the proposed method with respect to existing approaches include automation in the defect detection process and better defective area isolation through increased contrast. The algorithm is first proven by analyzing simulated thermal images, and then it is experimentally validated by scanning the surface of a CFRP composite plate with induced defects.

The performance and durability of electrochemical power systems are determined by a complex interdependency of many complex and interrelated factors, temperature and heat transfer being particularly important. This has led to an increasing interest in the use of thermal imaging to understand both the fundamental phenomena and effects of operation on the temperature distribution and dynamics in these systems. This review describes the application thermal imaging and related techniques to the study of electrochemical power systems with the primary focus on fuel cells and batteries. Potential opportunities and directions for future research are also highlighted, indicating the wide scope for further insights to be gleaned using infrared thermal imaging techniques.

Sports offer numerous benefits for physical and mental health, and current research focuses on a comprehensive evaluation of an athlete's well-being to enhance performance. Thermal imaging techniques are employed to observe athletes' activities in both psychological and physiological aspects. During competitive pursuits and exercise, thermal imaging records the athlete's temperature fluctuations. These temperature data, combined with other biometric information like heart rate, provide a more in-depth understanding of the athlete's state. To establish a connection with biomechanical performance, we consider muscle activation patterns and motion dynamics. Muscle activation during intense competition leads to increased metabolic heat, which is detectable via thermal imaging. For example, highly activated muscle groups may exhibit distinct temperature elevations. Motion dynamics, such as the speed and range of limb movements, also impact heat dissipation and distribution. Faster movements may cause more rapid heat convection, altering the thermal patterns captured. The collected thermal images undergo processing to reduce noise and enhance contrast. Specific regions are identified to extract relevant features, which are then analyzed for temperature patterns. Abnormal temperature distributions are detected using Gradient Optimized Recurrent Neural Networks (GO-RNN) to assess the athlete's physical and mental health. This analysis not only predicts potential injuries but also links thermal data with biomechanical performance. By correlating thermal imaging results with muscle activation and motion dynamics, we can develop more accurate performance evaluation models. This integration allows for a more precise understanding of an athlete's condition, enabling personalized training programs and better injury prevention strategies, ultimately leading to improved athletic performance and well-being.