Multi-source heterogeneous data fusion and multi-dimensional data correlation analysis system

Abstract

The invention discloses a multi-source heterogeneous data fusion and multi-dimensional data correlation analysis system, relates to the technical field of correlation analysis, solves the technical problem that the feasibility of data is reduced due to single data framework in the prior art, collects static multi-dimensional influence data of electromechanical equipment, improves the multisource of data construction, and improves the reliability of the data construction, and thereby an accurate basis is provided for data correlation analysis; herein, the collected data are continuously subjected to multi-dimensionalization, and an electromechanical equipment data framework is constructed, so that the data framework is comprehensive, and the accuracy of correlation data collection is improved; and then attribute calibration is performed on the data so as to provide a basis for correlation analysis of the data corresponding to the electromechanical equipment; according to the electromechanical equipment working condition analysis coefficient, whether the data of each dimension has influence is deduced, and the accuracy of data correlation analysis is improved, so that the situation of abnormal operation of the electromechanical equipment can be effectively prevented; meanwhile, the fault corresponding data can be quickly screened out when the electromechanical equipment breaks down.

Description

technical field [0001] The invention relates to the technical field of correlation analysis, in particular to a multi-source heterogeneous data fusion and multi-dimensional data correlation analysis system. Background technique [0002] Electromechanical equipment mainly includes power generation equipment and power supply equipment. Power generation equipment is mainly power plant boilers, steam turbines, gas turbines, water turbines, generators, transformers, etc. Power supply equipment is mainly transmission lines of various voltage levels, transformers, contactors, etc. In the operation process of electromechanical equipment, data analysis is often required, but the information from a single source cannot meet people's requirements for richness, real-time, accuracy and reliability of data information, which requires data fusion technology Estimates and decisions are derived from multi-source data to increase confidence in the data, improve reliability, and reduce uncerta...

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Problems solved by technology

[0002] Electromechanical equipment mainly includes power generation equipment and power supply equipment. Power generation equipment is mainly power plant boilers, steam turbines, gas turbines, water turbines, generators, transformers, etc. Power supply equipment is mainly transmission lines of various voltage levels, transformers, contactors, etc. In the operation process of electromechanical equipment, data analysis is often required, but the information from a single source cannot meet people's requirements for richness, real-time, accuracy and reliability of data information, which requires data fusion technology Deriving estimates and decisions from multiple sources of data to increase confidence in the data, improve reliability, and reduce uncertainty

[0003] However, in the existing technology, it is impossible to collect multi-dimensional data from electromechanical equipment, resulting in a single data frame, low feasibility of data collection, and low efficiency in the analysis of electromechanical equipment; at the same time, it is impossible to analyze multi-dimensional data in the data frame, The inability to accurately analyze the relationship between multi-dimensional data and electromechanical equipment leads to an increase in the failure rate of electromechanical equipment. At the same time, when the electromechanical equipment fails, it is impossible to accurately and quickly screen the influencing factors according to the characteristics, which increases the operating cost.

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