Evolution Of Virtual Instruments Measurement Uncertainty

Virtual instruments have more and more position in the instructions science. The paper take a title"Evolution of virtual instruments measurement uncertainty", is concentrate on the measurement uncertainty evaluation. There are important academic value and significant in the. The paper supported by the 2007 Gungdong Province Programs for Science and Technology Development in measuring technique of virtual instruments (2007A060304003) . On the basis of many references, the research progress at home and abroad of measurement uncertainty sources of virtual instruments and measurement uncertainty evolution methods, the research contents are determined. The main work includes the following parts:1. According to the structure of sensors and A/D converter, the sources of sensors is proposed to be nonlinear error, repeatability error, temperature drift, hysteresis etc, and the sources of A/D converter is proposed to be quantization error, gain, bias,differential nonlinear error,integral nonlinear error etc. According to the round off error in the computer basic operations and the error propagation law, the basic method, the model of the round off error in the computer complex operations was built. And the round off error of virtual instruments software was estimated.2. Based on bayesian theory, the formula and the evaluation process of bayesian measurement uncertainty is analyzed. According to the virtual instruments structure, the evaluation process of bayesian measurement uncertainty of the virtual instruments is analyzed, and the method to solve the difficult points. Based on the Monte Carlo method, the bayesian measurement uncertainty evaluation was simulated. Combined with the Monte Carlo method used in the measurement uncertainty propagation in the virtual instrument, the evaluation process of bayesian measurement uncertainty of the virtual instruments is given.3. According to difference of prior information, data and errors, the bayesian measurement uncertainty was implemented by the Winbugs software. With the measurement data, the simulation result was displayed in several different ways. Otherwise, the Winbugs progresses are able to be connected with Matlab by the special interface programs. Furthermore,the influence factors of the Monte Carlo simulation quality were discussed,and the sample size was proposed to be the main influence factor. The MC (Monte Carlo) relative error was proposed to be the parameter of the influence factors of the Monte Carlo simulation quality. With the parameter, the simulation quality was able to be controlled.Finally, the experiment was implemented in the pressure measuring system. The measurement uncertainty was evaluated by type A , type B methods and Bayesian method.