Abstract
The article considers one of the possible options for expanding the existing system for predicting icing on power line wires using fuzzy identifiers [2]. This option implies the use of secondary parameters that affect the ice formation process, such as atmospheric pressure at the station level, saturation deficit, cloudiness, weather at the observation time and the local geophysical parameters. The article describes the setting of a fuzzy identifier, with such input variables as the atmospheric pressure at the station level and the saturation deficit. The membership function distribution for input and output variables of this fuzzy identifier is shown. The rule database of this fuzzy identifier is given. The influence of the weighting factor on the perturbing effect on the output variable of this identifier is shown, and the weighting factor choice for it is also made.The modeling of the output variable (deposit diameter) was carried out by substituting statistical data for the Bratolyubovka, Bolshoy Shantar, Yelabuga, Nikolaevsk and Zeya stations into the model inputs. The average deviation of the simulated value from the statistical value was found for all the above stations. It is concluded that at these meteorological stations an additional influence on the process of icing is exerted by secondary parameters that have not yet been considered. It is shown that the introduction of additional controllers into the icing prediction system makes it possible to take into account additional parameters that affect the icing process. As the input data of these fuzzy identifiers, it would be advisable to consider the distance from the power line to the forest belt, height above sea level, cloudiness and precipitation, as the output data of these fuzzy identifiers, and also consider the wind speed. In conclusion, the article presents the resulting system for forecasting icing.
Keywords
modeling, forecasting, icing, power line, fuzzy identifier, fuzzy logic, membership functions, weather stations, statistical data, intelligent system
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