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APPLICATION OF SINGULAR SPECTRAL ANALYSIS IN CONTROL SYSTEMS OF TECHNOLOGICAL PROCESSES AND EXPLOSION SAFETY CONTROL OF FACILITIES.

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Title: APPLICATION OF SINGULAR SPECTRAL ANALYSIS IN CONTROL SYSTEMS OF TECHNOLOGICAL PROCESSES AND EXPLOSION SAFETY CONTROL OF FACILITIES.
Alternate Title: ЗАСТОСУВАННЯ СИНГУЛЯРНОГО СПЕКТРАЛЬНОГО АНАЛІЗУ В СИСТЕМАХ КЕРУВАННЯ ТЕХНОЛОГІЧНИМИ ПРОЦЕСАМИ ТА КОНТРОЛЮ ВИБУХОНЕБЕЗПЕЧНОСТІ ОБ'ЄКТІВ. (Ukrainian)
Authors: O. V., Holinko, M. O., Alekseev, V. I., Holinko, V. A., Zabelina
Source: Radio Electronics, Computer Science, Control; 2025, Issue 1, p209-219, 11p
Subject Terms: PROCESS control systems, TIME series analysis, COAL mining, RELIABILITY in engineering, RAW materials
Abstract: Context. The question of increasing the productivity of technological processes of extraction, processing and preparation of raw materials, improving product quality, reducing energy consumption, as well as creating safe working conditions during technological processes and preventing accidents is always quite relevant and requires the implementation of modern control and management systems. For the effective operation of such systems, it is important to pre-process and filter the data received from the sensors for monitoring the grinding processes and the explosive status of objects. One of the possible ways to increase the informativeness of data is the use of singular spectral analysis. Objective. Increasing the efficiency of technological process control systems and the reliability of explosive control systems of coal mines and oil and fuel complex facilities by processing and pre-filtering data received from sensors for monitoring grinding processes and the state of facilities. Method. To analyze the output signals of sensors used in control and management systems, the method of singular spectral analysis is used, which allows revealing hidden structures and regularities in time series by pre-filtering and data processing of acoustic, thermocatalytic, and semiconductor sensors. Results. A new approach to the management of technological processes of grinding raw materials in jet mills and control of the explosiveness of coal mines and objects of the oil and fuel complex is proposed, based on methods that allow to speed up the processing speed of sensor output data and improve the quality of information. It is shown that one of the promising methods that can be used for the pre-processing of time series of output data of sensors in control and control systems is the method of singular spectral analysis, the use of which allows filtering data, revealing hidden structures and regularities, and forecasting changes based on the analysis of previous information, identify anomalies and unusual situations, make more informed decisions and improve the processes of managing technological processes. Conclusions. The conducted experiments have confirmed the proposed software operability and allow recommending it for use in advancing both theoretical and practical aspects of process control systems through an enhanced singular spectral analysis (SSA) method for time series processing. This improved approach has been successfully demonstrated in real-world applications, including grinding processes in jet mills and explosion monitoring in coal mines and oil and fuel facilities. The implementation demonstrates a significant increase in data processing speed and information quality, which makes it particularly valuable for use in safety-critical industrial facilities. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
Description
Abstract:Context. The question of increasing the productivity of technological processes of extraction, processing and preparation of raw materials, improving product quality, reducing energy consumption, as well as creating safe working conditions during technological processes and preventing accidents is always quite relevant and requires the implementation of modern control and management systems. For the effective operation of such systems, it is important to pre-process and filter the data received from the sensors for monitoring the grinding processes and the explosive status of objects. One of the possible ways to increase the informativeness of data is the use of singular spectral analysis. Objective. Increasing the efficiency of technological process control systems and the reliability of explosive control systems of coal mines and oil and fuel complex facilities by processing and pre-filtering data received from sensors for monitoring grinding processes and the state of facilities. Method. To analyze the output signals of sensors used in control and management systems, the method of singular spectral analysis is used, which allows revealing hidden structures and regularities in time series by pre-filtering and data processing of acoustic, thermocatalytic, and semiconductor sensors. Results. A new approach to the management of technological processes of grinding raw materials in jet mills and control of the explosiveness of coal mines and objects of the oil and fuel complex is proposed, based on methods that allow to speed up the processing speed of sensor output data and improve the quality of information. It is shown that one of the promising methods that can be used for the pre-processing of time series of output data of sensors in control and control systems is the method of singular spectral analysis, the use of which allows filtering data, revealing hidden structures and regularities, and forecasting changes based on the analysis of previous information, identify anomalies and unusual situations, make more informed decisions and improve the processes of managing technological processes. Conclusions. The conducted experiments have confirmed the proposed software operability and allow recommending it for use in advancing both theoretical and practical aspects of process control systems through an enhanced singular spectral analysis (SSA) method for time series processing. This improved approach has been successfully demonstrated in real-world applications, including grinding processes in jet mills and explosion monitoring in coal mines and oil and fuel facilities. The implementation demonstrates a significant increase in data processing speed and information quality, which makes it particularly valuable for use in safety-critical industrial facilities. [ABSTRACT FROM AUTHOR]
ISSN:16073274
DOI:10.15588/1607-3274-2025-1-19