Relative humidity (RH) sensors and modules are becoming increasingly important in many processes of modern industry (e.g. in the manufacturing processes of ultrapure materials for electronics devices). However, at present the standards for RH sensors’ and modules’ calibration can not offer a better accuracy than a few tenth of%RH. This fact has a strong influence on the accuracy of calibration data, and in consequence, on the fitting of calibration equations. As a rule, many authors of handbooks on sensors and calibration (e.g. [1, 4]) only discuss the “classic" regression method for the" y on x" regression case. Some researchers have determined the calibration equations using the inverse regression:" x on y" (e.g. ). The inverse regression requires to meet the condition of negligible y’s measurement errors . An alternative to the regression methods is the minimax method of approximation. The goals of this work include providing proofs that it is reasonable to employ the minimax method to determining of calibration equations for RH sensors and modules, in comparison with the results obtained by the least-squares approximation method. In th[...]
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