Method for identifcation of linear dynamic measuring system based on preliminary nonlinear transformation of the input signal

The problem of the current identification of a linear dynamic measuring system with an unknown input signal under the influence of various destabilizing factors on the parameters of the system is considered. During identification, an additional channel is introduced for transforming the measured quantity in the spatial domain, the operator of which satisfies the condition of non-commutativity with the operator of the system under study. The solution to the problem of current identification is given for the linear dynamic characteristics of the main channel of the first-order measuring system. The method of modulating functions was used to exclude incorrect operations f differentiating the output signals of the structurally redundant measuring system in the process of current identification. Dependencies of the root mean square deviation of the given error of the input value estimation due the number of measurements at identification for different levels of the root mean square deviation of the measurement noise reduced to the input signal scale, as well as on the sampling frequency of the output signals of the structurally redundant measuring system with which the observation sample is formed during digital processing of the system output signal values in the computing device are presented. It is shown that the greatest identification accuracy is achieved with a quadratic transformation of the input signal in an additional channel of a structurally redundant measuring system, and the choice of a not too high sampling frequency of its output signals increases the stability of the identification algorithm. In this case, the dependence of the root mean square deviation of the reduced error in estimating the input value on the sampling frequency of the output signals of the structurally redundant measuring system has a minimum. The research results can be used to improve the accuracy of measuring systems in a dynamic measurement mode, as well as for metrological self-control of intelligent measuring systems.

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