Method of Data storing, collection and aggregation for definition of life-cycle resources of electromechanical equipment

Innovations and Prospects of Development of Mining Machinery and Electrical Engineering

矿业工程;电工学

Zhukovskiy, Y.^1 ; Koteleva, N.^1

St. Petersburg Mining University, 2, 21 Line of Vasilyevsky Island, St. Petersburg

199106, Russia^1

关键词: Electromechanical equipments;    Emergency situation;    Mineral and raw materials complexes;    Operating condition;    Operating parameters;    Technical conditions;    Technological conditions;    Technological process;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/87/3/032057/pdf
DOI  :  10.1088/1755-1315/87/3/032057

来源: IOP

【 摘 要 】

Analysis of technical and technological conditions for the emergence of emergency situations during the operation of electromechanical equipment of enterprises of the mineral and raw materials complex shows that when developing the basis for ensuring safe operation, it is necessary to take into account not only the technical condition, but also the non-stationary operation of the operating conditions of equipment, and the nonstationarity of operational operating parameters of technological processes. Violations of the operation of individual parts of the machine, not detected in time, can lead to severe accidents at work, as well as to unplanned downtime and loss of profits. That is why, the issues of obtaining and processing Big data obtained during the life cycle of electromechanical equipment, for assessing the current state of the electromechanical equipment used, timely diagnostics of emergency and pre-emergency modes of its operation, estimating the residual resource, as well as prediction the technical state on the basis of machine learning are very important. This article is dedicated to developing the special method of data storing, collection and aggregation for definition of life-cycle resources of electromechanical equipment. This method can be used in working with big data and can allow extracting the knowledge from different data types: the plants' historical data and the factory historical data. The data of the plants contains the information about electromechanical equipment operation and the data of the factory contains the information about a production of electromechanical equipment.