| Autor: |
V.N. Efanov, N.S. Ivanova, S.V. Zhernakov |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
2020 International Conference on Electrotechnical Complexes and Systems (ICOECS). |
| Popis: |
Discussed Intelligent technology that will allow the administrative technical and operational staff of the System operator and Federal grid company of Unified energy system, safe operation of power equipment according to factual technical condition. Studies show that the prediction of the technical condition is the most effective method of improving the operational reliability of various equipment. Diagnosis and prediction of the state allow timely decisions on the need and scope of preventive work. These works are aimed at the timely detection of possible defects and maintaining the operational state of the electric power facilities. The article shows that the systems for diagnosing and predicting the state of complex technical objects belong to the class of poorly structured systems. The limited amount of reliable data on the actual technical condition of the object under investigation leads to the fact that it is necessary to use both quantitative and qualitative indicators. Uncertainty in assessing the state of the object required the introduction of intelligent technologies focused on working with knowledge. To this end, the article proposes a generalized architecture of an intelligent system for assessing the technical state of complex technical objects of electroenergetics |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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