DocumentCode
2553637
Title
Process control system of roof disaster based on PDCA cycle
Author
Yongkui, Shi ; Guofeng, Song
Author_Institution
Coll. of Natural Resource & Environ. Eng., Shandong Univ. of Sci. & Technol., Qingdao, China
fYear
2009
fDate
21-23 Oct. 2009
Firstpage
199
Lastpage
203
Abstract
In order to control the whole process of roof disaster, first estimates the movement parameters of working face roof, calculates weighting intensity, chooses the method of roof support, calculates support parameters, predicts possible types of incidents and proposes preventive measures, according to geological conditions and design parameters. Then realizes auto-drawing which is depend on technical parameters, works out operational rules intelligently and ensures the implement of support design. At the same time, the system analyses the monitoring data of support quality and roof dynamic at actual working face, then makes contrast with the design results of the roof support design expert system, using the actual data to amend the expert system step by step, to complete "self-learning" function and realize PDCA cycle. It has proved that the system can control roof disaster very well, and it is of significance to coal mine safety production.
Keywords
coal; disasters; expert systems; learning (artificial intelligence); mining industry; occupational safety; process control; roofs; PDCA cycle; coal mine safety production; design expert system; geological condition; preventive measure; process control system; roof disaster; self-learning function; Control systems; Data analysis; Disaster management; Expert systems; Feedback; Geology; Monitoring; Process control; Production systems; Quality management; Operational Rules; PDCA; information feedback; process control; roof disaster; roof monitoring; support design;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Engineering and Engineering Management, 2009. IE&EM '09. 16th International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-3671-2
Electronic_ISBN
978-1-4244-3672-9
Type
conf
DOI
10.1109/ICIEEM.2009.5344605
Filename
5344605
Link To Document