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The Physics of Human Thermography
Published in James Stewart Campbell, M. Nathaniel Mead, Human Medical Thermography, 2023
James Stewart Campbell, M. Nathaniel Mead
The term “emissivity” in thermal imaging refers to the ability of a surface to emit or absorb radiation within 9–10-μm infrared range. The range of emissivity runs from 1.0 (the ideal emitter/absorber) to 0.0 (the ideal reflector). In physics, a blackbody is an object that has an emissivity of 1.0. None of the incident radiation is reflected from or passes through a perfect blackbody. Thus, a blackbody completely absorbs all radiant energy reaching it, and simultaneously emits radiant energy. If not otherwise heated or cooled, it eventually attains a temperature equal to its environment and then maintains that energy balance.
Utilization of Iron Ore Tailings in Bricks
Published in Karra Ram Chandar, B. C. Gayana, P. Shubhananda Rao, Mine Waste Utilization, 2022
P. Shubhananda Rao, Karra Ram Chandar
Emissivity is a term used to describe the energy-emitting characteristics of materials. Most organic materials and painted or oxidized surfaces have an emissivity of 0.98, and the details of infrared thermometer are shown in Table 6.18. Metal surfaces or shiny materials have a lower emissivity (www.primusthai.com).
Energy Basics
Published in Stan Harbuck, Donna Harbuck, Residential Energy Auditing and Improvement, 2021
Remember that metals are good conductors of heat. They have a high K-value and a low R-value, and cannot be used as insulators. For instance, if you grab a hot piece of metal, the heat from the metal easily transfers to your hand. It feels hot, and you pull your hand away to avoid being burned. In the case of radiation, metals, especially shiny ones, tend to be poor emitters of radiation energy. They can also reflect solar rays well and that is why some of the best roof coatings are made of aluminum or other appropriate metals. Metals have a low emissivity coefficient. This is the reason a thin metal layer can be on the underside of roof decking to help keep heat from the shingles from transferring into the attic space as easily, as long as no insulation is touching the barrier. Metals are some of the few common substances that reflect both visible and infrared radiation back away from the building. However, nothing can touch that thin metal layer where it faces the inside, or the benefit of being a poor radiation emitter is lost by allowing its high conductivity to transfer heat to whatever it is touching.
Vibration and infrared thermography based multiple fault diagnosis of bearing using deep learning
Published in Nondestructive Testing and Evaluation, 2023
Tauheed Mian, Anurag Choudhary, Shahab Fatima
Here, Q is the total radiated energy per unit area, where ε is called emissivity, is called the Stefan-Boltzmann constant with an approximate value of 5.67 x 10−8 Wm−2 K−4, and T is the absolute temperature. Emissivity is a material property that is different for different materials and is important for accurate temperature measurement as well as capturing accurate thermal images [47]. The value of emissivity for a perfectly black body is considered as 1. The factors associated with thermography are broadly mentioned in three categories as procedural, technical (material properties, distance, reflected temperature, specifications of camera etc.), and environmental (atmospheric temperature, humidity etc.). The heatmap generated using IRT can be used as an important source of information for diagnosing bearing faults. Thermal images are captured with the help of a thermal camera. This camera basically composed of the optical components (including lens, mirrors, etc.), detector elements, cooling arrangments, and related electronics. The present work extracted the thermal images of bearing from the complete frame by concentrating on RoI, as shown in Figure 4. The raw thermal image can be seen as a temperature map generated through the FLIR tool. The pixel values of RGB thermal are represented in Figure 4. It is clear from the map that the difference at pixel levels makes it a convenient tool for the diagnosis of different fault conditions.
Simultaneous retrieval of land surface temperature and emissivity from the FengYun-4A advanced geosynchronous radiation imager
Published in International Journal of Digital Earth, 2022
Weihan Liu, Jiancheng Shi, Shunlin Liang, Shugui Zhou, Jie Cheng
To obtain the EMC/WVD coefficients of the modified WVS method, representative emissivity spectra consisting of 157 samples were selected from the ASTER spectral library (Baldridge et al. 2009) and MODIS UCSB spectral library (http://g.icess.ucsb.edu/modis/EMIS/html/em.html), which contains typical emissivity spectra such as the emissivity spectra of water, snow/ice, vegetation, soils, sands, and rock. The dynamic range of emissivity is between 0.65 and 1. The selected emissivity spectra were convolved with AGRI’s spectral response function for each channel and then divided into six groups based on the minimum channel emissivity: [0.96,1], [0.91,0.96], [0.86,0.91], [0.81,0.86], [0.76,0.81], and [0.71,0.76]. The simulated LSTs are calculated by adding the differences T set as −10, −5, 0, 5, 10, and 15 K to the surface air temperature. We set 6 viewing angles between 0-75° at an interval of 15°. In total, 5,254,476 simulations (5578 profiles×157 spectra× 6 T) were generated with MODTRAN 5.2 for each viewing angle. With the simulated surface and TOA BT and the TPW of each SeeBor profile, the EMC/WVD coefficients in (3) were derived by using a linear least squares method for each viewing zenith angle and each group of minimum channel emissivities. The fitting results of the EMC/WVD coefficients for graybody pixels are summarized in Table 3.
Investigating the heat distribution on welded parts from a TIG welding operation in a railcar manufacturing environment
Published in Cogent Engineering, 2022
Walter Thabo Seloane, Khumbulani Mpofu, Boitumelo Ramatsetse, Dithoto Modungwa
The experimental test results obtained from the thermocouples imbedded in the fixture block as well as the thermal distribution histograms from the Testo thermograph IR camera taken immediately after the welding cycle for the respective parts are presented in this section. Testo thermograph analyser uses an Infrared (IR) camera to carry out a wide range of different thermal imaging tasks. Crystal clear thermal images are taken from a wide angle; parallel digital real images of the same measuring object with manual or motor-driven focusing. The thermograph analyser measures the temperature by recording the IR energy emitted by the object. The camera can measure high temperatures of around 1200 °C safely from a minimum safety distance of around 200 mm. Different materials radiate different amounts of IR energy at the same temperature. This efficiency factor is called the emissivity, which is defined as the fraction of radiation emitted by an object as compared to the radiation emitted by a perfect radiator, called the blackbody, at the same temperature. The emissivity may vary from close to 0 (for a highly reflected mirror) to almost 1 (for a blackbody). The control panel with a PLC-based data acquisition system linked with thermocouples type K was used to measure the amount of heat generated on the fixture locating block at the respective stations and the temperature trends at each station were monitored on the control panel screen. The recorded cycle times for all the welded parts are tabulated in Table 3. These cycle times served as inputs for the FEA analysis.