Software and algorithms for information processing at resistance thermometers calibration
The paper is devoted to parametric identification problem and estimation of the temperature error in the 
 calibration of resistance thermometers. The operating principle of the resistance thermometers is based on the dependence of 
 the electrical resistance on the temperature. In the operation of the device, the resistance is directly measured quantity. Since, 
 it is required to obtain the temperature values from the resistance measurements. The mathematical model describing the de-pendence temperature on the resistance is given by the system of equations with unknown parameters. To solve formulated 
 problem, the calibration of instruments is performed. The goals of calibration are to obtain the parameters of the model and to 
 estimate the temperature errors. To solve the parametric identification problem, we propose a method based on the Tikhonov 
 regularization. Approach for estimation of the temperature error is also expounded. The proposed methods provide the basis 
 for development the methods of the information processing in the calibration. The processing results are the basis for 
 determining of the criteria for choosing optimal parameters in the calibration process. In the second part of the paper we 
 describe the software to implement the proposed algorithms. The proposed methods and software were used for the 
 computational experiments and for the creation of software for experimental data processing.