Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Coal mining accident prediction model determination and monitoring method, storage medium and electronic equipment

A technology of accident prediction and determination method, applied in the field of coal mine safety production, can solve the problems of low safety, inability to reduce the occurrence rate of coal mine accidents, inability to predict coal mine accidents in advance, etc., to achieve the effect of improving safety and reducing the occurrence rate of coal mine accidents

Pending Publication Date: 2018-11-23
CHINA SHENHUA ENERGY CO LTD
View PDF3 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to overcome the inability to predict coal mine accidents in advance, the inability to reduce the incidence of coal mine accidents, and the deficiencies of low safety in the prior art, and provide a coal mine accident prediction model determination and monitoring method, storage medium and electronic equipment

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Coal mining accident prediction model determination and monitoring method, storage medium and electronic equipment
  • Coal mining accident prediction model determination and monitoring method, storage medium and electronic equipment
  • Coal mining accident prediction model determination and monitoring method, storage medium and electronic equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0052] Such as figure 1 as shown, figure 1 It is a work flow diagram of a coal mine accident prediction model determination method provided by an embodiment of the present invention, including:

[0053] Step S101: Analyze the historical accident feature information obtained, and generate an accident feature set corresponding to the type of coal mine accident. The accident feature set includes historical accident feature information and accident feature value information;

[0054] Specifically, the characteristic information of historical accidents includes gas, concentration, accumulation, supercapacity, production and other characteristics that can cause coal mine accidents. The feature information of historical accidents can be obtained by parsing historical accident case documents based on the general dictionary and coal mine dictionary by using Vector Space Model (VSM), or by direct input manually.

[0055]Accident characteristic value information refers to the number of...

Embodiment 2

[0070] Such as figure 2 as shown, figure 2 It is a work flow diagram of a method for determining a coal mine accident prediction model provided by an optional embodiment of the present invention, including:

[0071] Step S201: Classify the historical accident feature information according to the coal mine accident type to generate a first accident feature subset;

[0072] Step S202: According to the stop word dictionary stored in advance, remove stop words for the historical accident characteristic information in the first accident characteristic subset, generate the second accident characteristic subset;

[0073] Step S203: According to the non-keyword dictionary stored in advance, remove non-keywords to the historical accident feature information in the second accident feature subset, and generate the accident feature set;

[0074] Step S204: Carry out word frequency statistics on the historical accident feature information in the accident feature set to generate the acc...

Embodiment 3

[0084] Such as image 3 as shown, image 3 It is a work flow diagram of a coal mine accident monitoring method provided by an embodiment of the present invention, including:

[0085] Step S301: Analyze the historical accident feature information obtained, and generate an accident feature set corresponding to the coal mine accident type, the accident feature set includes historical accident feature information and accident feature value information;

[0086] Step S302: According to the accident feature value information and the pre-stored feature word frequency threshold information, the historical accident feature information is correlated and analyzed to generate accident key element information;

[0087] Step S303: Analyzing the accident key element information to generate key element value information;

[0088] Step S304: According to the key element value information and the pre-stored association rules, carry out association analysis on the accident key element informat...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a coal mining accident prediction model determination and monitoring method, a storage medium and electronic equipment. The method comprises the steps of analyzing acquired historical accident feature information to generat an accident feature set corresponding to a coal mining accident type, wherein the accident feature set comprises historical accident feature informationand accident feature value information; according to the accident feature value information and pre-stored feature word frequency threshold information, performing association analysis on the historical accident feature information to generate accident key factor information; analyzing the accident key factor information to generate key factor value information; according to the key factor valueinformation and a pre-stored association rule, performing association analysis on the accident key factor information to generate a key factor frequent item set; and according to the key factor frequent item set, generating an accident prediction mathematic model by using a BP neural network. According to the method, medium and equipment provided by the invention, through analyzing and performingassociation analysis on the historical accident feature information, the accident prediction mathematic model is generated, and the secure production of the coal mine is monitored in real time.

Description

technical field [0001] The invention relates to the technical field of coal mine safety production, in particular to a coal mine accident prediction model determination and monitoring method, a storage medium and electronic equipment. Background technique [0002] Accidents in coal mines refer to accidents that occur during coal mining, usually resulting in a high risk of casualties. At least thousands of people die in coal mine accidents every year in the world. Common types of accidents in coal mines include gas accidents, fire accidents, flood accidents, roof accidents, electromechanical accidents, transportation accidents, blasting accidents and other accidents. [0003] At present, the existing coal mine safety management system is mainly a post-accident analysis system for coal mine accidents, which usually conducts subjective analysis of accidents based on the knowledge and experience of coal mine safety experts to determine the cause of accidents. However, the exist...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06Q10/04G06Q50/02G06N3/04
CPCG06Q10/04G06Q50/02G06N3/045
Inventor 李东张光德周勇张小兵郭进伟张占国孙小平杨波刘生优郑源志
Owner CHINA SHENHUA ENERGY CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Eureka Blog
Learn More
PatSnap group products