دانلود مقاله ISI انگلیسی شماره 6265
ترجمه فارسی عنوان مقاله

مطالعه درباره مدل هشدار دهنده زود هنگام مهندسی معدن زغال سنگ با تحلیل سلسله مراتبی فازی

عنوان انگلیسی
Study on Early Warning Model of Coal Mining Engineering with Fuzzy AHP
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
6265 2012 6 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Systems Engineering Procedia, Volume 5, 2012, Pages 113–118

ترجمه کلمات کلیدی
مهندسی معدن ذغال سنگ - هشدار اولیه ایمنی - فرآیند تحلیل سلسله مراتبی - ریاضیات فازی -
کلمات کلیدی انگلیسی
Coal mining engineering,Safety early warning,Analytic Hierarchy Process,Fuzzy mathematics,
پیش نمایش مقاله
پیش نمایش مقاله  مطالعه درباره مدل هشدار دهنده زود هنگام مهندسی معدن زغال سنگ با تحلیل سلسله مراتبی فازی

چکیده انگلیسی

The safety issue of coal mining engineering is very important to coal industry. According to our coal mine enterprises’ safe characteristics, this paper analyzed the risk factors of coal mining engineering and studied the safety problem of “human-machine-environment” system. The risk factors of coal mining engineering are divided to natural geological factors, personnel factors, equipment factors and management factors. Based on the fuzzy mathematics and these factors, the safety early warning model of coal mining engineering is constructed by using the fuzzy AHP method. Through the use of early warning model, we can find the risk sources and hidden danger of mining operations in time. Combined with a production mine, this early warning model is applied to the mining operations process. The results show that this early warning model is effective to prevent the accident.

مقدمه انگلیسی

Coal mine safety management is very important to coal mining engineering. Many research works about coal mine safety management are done by Chinese scholars and the coal mine safety management has been greatly improved in recent years. But according to the overall development level of coal industry, the Chinese coal mine enterprise management is in the empirical accident management stage and can't meet the practical needs by enterprise production actions. It is an urgent task to break island state of security information and excavate the valuable information from the feedback data of coal mining system[1]. Based on the fuzzy mathematics, this paper constructs a safety early warning model of coal mining engineering. Combining safety factors of coal mine, the safety early warning model can be used to improve safety management situation of coal mine enterprises. The research object of safety early wa rning is “human-machine-environment” system. By using modern tools and technology, we can get all kinds of safety related data and carry out a series of activities such as assessment, review, classification, analysis and monitoring, etc. Then the security warning signals in different stages can be got[2]. Base on the risk signals are conveyed in time, we can get the safety data about coal mining engineering with the safety early warning model. By contrast wit the risk management threshold, we can adopt different control behaviors to avoid accidents.

نتیجه گیری انگلیسی

The safety issue of coal mining engineering is very important to coal industry. According to the coal mine enterprises' safe characteristics, this paper introduced early warning mechanism to the safety management of coal mine. By using the fuzzy AHP method, the index system about coal mine safety and the safety early warning model of coal mining engineering are established. According to our coal mine en terprises' safe characteristics, this paper analyzed the risk factors of coal mining engineering and studied the safety problem of “human-machine-environment” system. The risk factors of coal mining engineering are divided to natural geological factors, personnel factors, equipment factors and management factors. Based on the fuzzy mathematics and these factors, the safety early warning model of coal mining engineering is constructed by using the fuzzy AHP method. Combined with the production mine of Huangling Group, this early warning model is applied to the mining operations process. The results show that this earlywarning model is effective to prevent the accident.