SOFTWARE AND HARDWARE COMPLEX OF AUTOMATED PROCESS CONTROL SYSTEMS FOR GAS-GENERATING INSTALLATIONS

Author(s):  
Nikolai Aleksandrovich Avtushenko ◽  
Gennady Sergeyevich Lenevsky
Author(s):  
Aleksey Sergeevich Dobrynin ◽  
Mikhail Yur'evich Gudkov ◽  
Roman Sergeevich Koynov

The continuous development of automated control systems for industrial facilities leads to the emergence of more advanced and complex control algorithms. A natural consequence of the development of control systems (CS) is the use of more complex technical means: sensors, controllers, SCADA and MES systems. Ultimately, the saturation of systems with additional software and hardware leads to a decrease in manageability in general, since software needs to be updated, equipment often fails, needs replacement, etc. Thus, approaches aimed at creating separate, autonomously functioning subsystems are becoming a thing of the past. An integrated, multi-level joint management of the entire infrastructure of the process control system is needed, from the technological facility to the technical infrastructure, which is closely tied to the facility. The article discusses the issues of constructing top-level control subsystems for the process control system, when it is necessary to control directly the software and hardware as part of the process control system. As research methods, simulation and computer modeling was used, which made it possible to evaluate the effectiveness of the proposed approaches and management methods. Also, the research results were verified through the pilot implementation of an automated incident management system based on the proposed approaches in the process of managing a complex technologically object. The novelty of the research lies in the proposed approach to incident management in automated process control systems, which makes it possible to improve the quality of management, reduce management costs, and predict (in some cases) the occurrence of new incidents and take measures to prevent them. Studies have shown the feasibility of using the proposed approach to control complex non-stationary automation systems.


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Author(s):  
D. Vasilchenko ◽  
A. Budilovskaya

This article discusses the use of Internet architecture in centralized automated process control systems for the purpose of monitoring and managing geographically distributed objects. The hardware components of the proposed architecture are described and the required functions are formulated. The methods of implementing these functions of centralized control systems based on this architecture are proposed: using internal algorithms of SCADA systems, or using microprocessor subsystems. The difficulties that are likely to be encountered when implementing all the required functions in the system being developed are described.


Vestnik MEI ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 78-87
Author(s):  
Edik K. Arakelyan ◽  
◽  
Ivan A. Shcherbatov ◽  

The uncertainty of the source information is used to solve key tasks in an intelligent automated thermal process control system affects the calculation of control actions, the implementation of equipment optimal operating modes and, as a result, leads to degraded reliability. As a rule, this type of information can be qualitative (the use of expert knowledge) or quantitative in nature. In this regard, it is extremely important to reduce the impact of uncertainty. The aim of the study is to identify the types and origins of uncertainty in the source information used by an intelligent automated process control system and to develop approaches to reduce its impact on the reliability of power equipment operation. The approaches used to ensure the specified indicators of reliability, efficiency and environmental friendliness in modern intelligent automated process control systems are based on predictive strategies, according to which the technical condition of equipment and specific degradation processes are predicted. This means that various types of uncertainty can have a significant negative impact. To reduce the influence of uncertainty of the initial information that affects the reliability of power equipment operation, the use of artificial neural networks is proposed. Their application opens the possibility to predict the occurrence of equipment defects and failures based on retrospective data for specified forecast time intervals. A method for reducing the impact of anomalies contained in the source information used in an intelligent process control system for energy facilities is demonstrated. Data omissions and outliers are investigated, the elimination of which reduces the impact of uncertainty and improves the quality of solving key problems in intelligent automated process control systems. Experimental studies were carried out that made it possible to identify the mathematical methods for removing omissions and anomalies in the source information in the best way. Methodological aspects of eliminating various types of uncertainty that exist in managing of power facilities by means of intelligent automated process control systems at the key stages of the power equipment life cycle are described.


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