In this paper, a concept of an intelligent temperature transducer (ITT) featuring a new autocalibration procedure cooperating with a platinum resistance temperature detector (RTD) is presented. This procedure is based on the application of resistors representing the standards of the measured temperature. The effect of this procedure is the minimization of linearity errors of the ITT processing characteristic, including the RTD, and the minimization of the ITT offset and gain errors. In the adopted ITT solution, the compensation of the RTD wires resistance is applied. The simulation and experimental research results, which confirm the high effectiveness of this procedure, are presented. The uncertainty of temperature measurement by means of the Monte Carlo method is evaluated and experimental research results, confirming the possibility of measuring temperature within a range of 0 °C-200 °C with a 0.03 °C uncertainty, are presented.

The paper is concerned with issues of the estimation of random variable distribution parameters by the Monte Carlo method. Such quantities can correspond to statistical parameters computed based on the data obtained in typical measurement situations. The subject of the research is the mean, the mean square and the variance of random variables with uniform, Gaussian, Student, Simpson, trapezoidal, exponential, gamma and arcsine distributions.

The article presents an intelligent temperature transducer (ITT), which can work with a two-wire or a three-wire platinum resistance temperature detector (RTD). The ITT design allowed for compensation of the RTD’s lead wire resistance. The ITT used the author’s auto-calibration procedure, which minimized linearity errors of the ITT and RTD processing characteristics, ITT offset and gain errors, and errors resulting from changes in the ITT operating conditions concerning the nominal conditions. The presented results of a simulation and experimental studies confirmed the high effectiveness of this procedure. The determined uncertainty of temperature measurement using the Monte Carlo method and the obtained experimental results confirmed the possibility of measuring temperatures in the range of 0–200 °C with an expanded uncertainty of 0.02 °C at a 99% confidence level.

The article presents new tools for investigating the statistical properties of the harmonic signal autocorrelation function (ACF). These tools enable...

The article evaluates the accuracy of the estimating results of the mean value of a sinusoidal voltage. For this purpose, a mean value estimator calculated from voltage samples has been used. The bias, the variance and the mean squared error of an estimator have been determined.