Safety warning of coal mining face based on big data association rule mining

摘要

The hidden danger of accidents seriously threatens the safety of the working face of coal mining. By digging the internal association rules of hidden danger, the construction of safety warning rule base can improve the ability of coal mining enterprises to deal with hidden danger as soon as possible. Coal mining work face hazards are analyzed with three types of hazard theory, and the types, attributes and dimensions of hidden accidents in coal mining face are studied, combined with the production practice of coal mining working face, and referring to the thought and method of “5W1H”. Then, the structure of safety early warning knowledge base is studied and the key of safety early warning knowledge base is put forward. On this basis, the paper designs the mining model of mining face data to mine the association rules of accident hidden danger data. The empirical analysis shows that the rule base of safety warning can be used to deal with hidden danger of coal mining working face, and realize the early warning of hidden danger of accident, providing a method for dealing with hidden danger of coal mine accident and managing dangerous source. .