I.A. Skatkov, D.V. Moiseev
Sevastopol State University, RF, Sevastopol, Universitetskaya St., 33
The paper focuses on the construction of separate model representations in the study of reliability of data obtained from environmental monitoring systems. Modern systems for monitoring environmental parameters are complex complexes of different technical and software tools. Special requirements to the quality of monitoring systems arise when they are used as subsystems in systems of responsible application, monitoring the state of critical energy facilities, mining, transport, and chemical production processes. One of the main reasons for reducing the reliability of such data is degradation processes in the primary meter, which are often installed in aggressive environments with an unsatisfactory set of parameters in the places where they are located. As a result of degradation effects, there is a significant decrease in the accuracy of primary meters, up to complete failures. An approach is described that allows increasing the duration of continuous operation of the system for monitoring environmental parameters. The basis of this approach is adaptive correction of primary meter readings in the event of a decrease in their accuracy due to degradation failures. It is noted that in order to identify interdependencies in such a system, it is necessary to conduct a simulation of the adaptation process in the system for monitoring environmental parameters, and the task is to create such a model. The structure and equations of such a system are proposed, and the task of creating a simulation model of the system is set.
Thus, the main task of the proposed approach is to extend the intervals between repairs of environmental monitoring systems. This is achieved by extending the service life of primary meters in the event of their degradation failures. This resource extension is achieved by creating an additional feedback channel with adaptive parameters in the system.
Keywords: simulation modeling, primary sensor, degradation failure, adaptive correction.
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