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Featured ApplicationRadiation thermometry of real objects under real conditions.Despite great technical capabilities, the theory of non-contact temperature measurement is usually not fully applicable to the use of measuring instruments in practice. While black body calibrations and black body radiation thermometry (BBRT) are in practice well established and easy to accomplish, this calibration protocol is never fully applicable to measurements of real objects under real conditions. Currently, the best approximation to real-world radiation thermometry is grey body radiation thermometry (GBRT), which is supported by most measuring instruments to date. Nevertheless, the metrological requirements necessitate traceability;therefore, real body radiation thermometry (RBRT) method is required for temperature measurements of real bodies. This article documents the current state of temperature calculation algorithms for radiation thermometers and the creation of a traceable model for radiation thermometry of real bodies that uses an inverse model of the system of measurement to compensate for the loss of data caused by spectral integration, which occurs when thermal radiation is absorbed on the active surface of the sensor. To solve this problem, a hybrid model is proposed in which the spectral input parameters are converted to scalar inputs of a traditional scalar inverse model for GBRT. The method for calculating effective parameters, which corresponds to a system of measurement, is proposed and verified with the theoretical simulation model of non-contact thermometry. The sum of effective instrumental parameters is presented for different temperatures to show that the rule of GBRT, according to which the sum of instrumental emissivity and instrumental reflectivity is equal to 1, does not apply to RBRT. Using the derived models of radiation thermometry, the uncertainty of radiation thermometry due to the uncertainty of spectral emissivity was analysed by simulated worst-case measurements through temperature ranges of various radiation thermometers. This newly developed model for RBRT with known uncertainty of measurement enables traceable measurements using radiation thermometry under any conditions.
RESUMO
The Covid-19 pandemic has altered the way people view online learning, which has experienced explosive growth since the pandemic and quickly cultivated the habit of online learning among the students. Online learning is not limited by time or space, and students can learn the courses repeatedly. Despite these advantages, it still has serious limitations in face of hardware-related courses like embedded technology, because it is not likely to provide opportunities for close-up observation of the real objects or any hands-on experience. Therefore, the learning effect will be greatly compromised. This paper proposed a solution for online learning of embedded technology course. It introduced the objective and content design of the course, the integration of ideological and political elements into the course, the teaching platforms that have been used as well as the concrete implementation process of online learning of the course, and it also statistically examined the effect of online learning. © 2022 ACM.