Mine potential safety hazard identification and early warning system based on big data analysis

Abstract

The invention discloses a mine potential safety hazard identification and early warning system based on big data analysis, and the system comprises a big data collection module which is used for collecting potential safety hazard data of different sources and different formats; a big data standardization preprocessing module which is used for performing extraction, cleaning and standardization preprocessing on the collected potential safety hazard data; a big data analysis module which is used for analyzing the preprocessed data on the basis of the data mining model library and performing structured storage on an analysis result; and a big data visualization module which is used for visually presenting a big data analysis result, so that a security manager can conveniently carry out risk early warning and scientific decision making. According to the invention, an intelligent safety analysis and early warning system with intelligent analysis, identification, mining and knowledge discovery as core contents is constructed, and support can be provided for mine safety risk identification, hazard source grading, safety prevention and control strategies and safety emergency disposal.

Description

technical field [0001] The invention relates to the technical field of mine safety management, in particular to a mine safety hazard identification and early warning system based on big data analysis. Background technique [0002] Mine safety management usually uses the hidden safety hazard inspection data accumulated in the production process of mines as the original data source. These hidden safety hazard inspection data contain a large amount of effective information such as the time, location, and description of hidden dangers. However, the safety inspection data has problems such as random records, irregular terms, many industry idioms, and unclear problem descriptions, which limit its deeper and effective use. At the same time, the particularity and complexity of mine safety production management make the corresponding mining safety There are many information dimensions, huge content, and multi-level polarization. Therefore, under the traditional model, it is difficult...

AI Technical Summary

Problems solved by technology

Limited by the methods and functions of traditional data analysis, these security data are only used to complete simple security problem processing, report analysis and data statistics. The life cycle of the data is quite short. Accumulated in the form of a large amount of historical data, which has not played a supporting role in increasing the pertinence of hidden danger investigations and visually describing the distribution and correlation of hidden safety hazards.

Images