Abstract
The paper discusses and analyzes the application of fuzzy logic methods for self-calibration of measuring devices. In particular, the principles of constructing measurement devices based on fuzzy logic, based on linguistic variables and rules, are considered, which makes it possible to take into account various conditions and requirements of production processes. To illustrate the effectiveness of the proposed methods, the results of experiments on measuring and classifying process parameters using fuzzy logic algorithms are presented. The study also covered fuzzy rule methods for evaluating and processing measurement data based on expert knowledge and linguistic variables. Fuzzy rule-based systems are shown to effectively account for uncertainties and variability in input data, allowing accurate decisions to be made based on complex rules formulated by experts in the relevant measurement fields.
First Page
183
Last Page
187
References
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Recommended Citation
Ruziev, U.A. and Shodiev, M.K.
(2024)
"SELF-CALIBRATION OF SMART SENSORS BASED ON FUZZY LOGIC,"
Chemical Technology, Control and Management: Vol. 2024:
Iss.
5, Article 31.
DOI: https://doi.org/10.59048/2181-1105.1651