SELF-CALIBRATION OF SMART SENSORS BASED ON FUZZY LOGIC

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.

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Publication Details

Journal
Himičeskaâ tehnologiâ. Kontrolʹ i upravlenie/Chemical Technology. Control and Management
Published
2024-10-24
DOI
https://doi.org/10.59048/2181-1105.1651
Primary Topic
Sensor Technology and Measurement Systems
Type
article
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article

SELF-CALIBRATION OF SMART SENSORS BASED ON FUZZY LOGIC

Marufjon Shodiev, Umidjon Ruziev
Himičeskaâ tehnologiâ. Kontrolʹ i upravlenie/Chemical Technology. Control and Management
Sensor Technology and Measurement Systems
article

SELF-CALIBRATION OF SMART SENSORS BASED ON FUZZY LOGIC

Marufjon Shodiev, Umidjon Ruziev
article en

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.

Himičeskaâ tehnologiâ. Kontrolʹ i upravlenie/Chemical Technology. Control and ManagementVol. 2024(5)
Affordable and clean energy
Openalex Percentile: Top 71%
Sensor Technology and Measurement Systems
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