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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics
Ansabekova, Gulbakyt
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Computer Science & IT Electrical & Electronics Engineering

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Development of intelligent protection and automation control systems using fuzzy logic elements Ansabekova, Gulbakyt; Sarsikeyev, Yermek; Abdimuratov, Zhubanyshbai; Appakov, Nurbol; Kaliyev, Zhanybek; Umurzakova, Anara; Sarbassova, Nurbanu; Zhumatova, Assel
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp556-565

Abstract

In this article, the causes of technological disturbances in electrical systems are considered, and several characteristic disadvantages of the protection and automation of elements of electrical systems are highlighted. The tendency to decrease the reliability of relay protection associated with the transition from analog to digital types of protection is substantiated. Based on the studied examples, the use of fuzzy logic in protections, the expediency of using fuzzy logic elements in protection devices, and the automation of electrical systems to identify types of short circuits are justified. This article analyzes the most common damages and presents the results of modeling an electrical system with transformer coupling, where all types of asymmetric short circuits were initiated. The dynamics of changes in the symmetrical components of short-circuit currents of the forward, reverse, and zero sequences are determined. Rules have been created for the identification of asymmetric types of short circuits. An algorithm of protection and automation operation using fuzzy logic elements has been developed. The proposed algorithm of protection and automation will reduce the time to determine the type of damage and trigger protections.
Thermal mode modeling using neural network technologies and the finite element method Mussabekov, Nazarbek; Utepbergenov, Irbulat; Kaliyev, Zhanybek; Issayeva, Zhazira; Ybytayeva, Galiya; Ansabekova, Gulbakyt; Karnakova, Gayni; Butabaeva, Karlygash
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.11268

Abstract

This study presents the analysis and modeling of the thermal regime of a furnace lining at an industrial copper smelting facility using a combined approach based on neural network (NN) technologies and the finite element method (FEM). Experimental temperature data were collected from a laboratory setup equipped with three thermocouples (TP-2488/1 and TCRosemount 0065), with a sampling frequency of 1 Hz over a total duration of 5 hours, resulting in 18,000 measurement points. The measurement uncertainty of the thermocouples did not exceed ±1.5 °C. These data were used both for model development and for validating the numerical FEM simulations. A feedforward neural network was trained using 70% of the dataset, while 15% and 15% were used for validation and testing, respectively. The prediction error of the neural network remained within 3% with a 95% confidence interval of [2.6%, 3.4%]. The results show that the proposed hybrid approach improves temperature prediction accuracy and reduces static control error by 15% when combined with a proportional-integral controller. The methodology demonstrates significant potential for improving thermal process stability and reducing energy consumption in high-temperature metallurgical systems.
Co-Authors Abdimuratov, Zhubanyshbai Appakov, Nurbol Butabaeva, Karlygash Issayeva, Zhazira Kaliyev, Zhanybek Karnakova, Gayni Mussabekov, Nazarbek Sarbassova, Nurbanu Sarsikeyev, Yermek Umurzakova, Anara Utepbergenov, Irbulat Ybytayeva, Galiya Zhumatova, Assel