In our study, entropy weight coefficients, based on Shannon entropy, were determined for an attribute recognition model to model the quality of groundwater sources. The model follows the theory previously proposed by ...In our study, entropy weight coefficients, based on Shannon entropy, were determined for an attribute recognition model to model the quality of groundwater sources. The model follows the theory previously proposed by Chen Q S. In the model, firstly, the author establishes the attribute space matrix and determines the weight based on Shannon entropy theory; secondly, calculates attribute measure; thirdly, evaluates that with confidence criterion and score criterion; finally, an application example is given. The results show that the water quality of the groundwater sources for the city comes up to the grade II or III standard. There is no pollution that obviously exceeds the standard and the water can meet people’s needs .The results from an evaluation of this model are in basic agreement with the observed situation and with a set pair analysis (SPA) model.展开更多
As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.D...As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.Due to the many factors affecting water inrush and the complicated water inrush mechanism,many factors close to water inrush may have precursory abnormal changes.At present,the existing monitoring and early warning system mainly uses a few monitoring indicators such as groundwater level,water influx,and temperature,and performs water inrush early warning through the abnormal change of a single factor.However,there are relatively few multi-factor comprehensive early warning identification models.Based on the analysis of the abnormal changes of precursor factors in multiple water inrush cases,11 measurable and effective indicators including groundwater flow field,hydrochemical field and temperature field are proposed.Finally,taking Hengyuan coal mine as an example,6 indicators with long-term monitoring data sequences were selected to establish a single-index hierarchical early-warning recognition model,a multi-factor linear recognition model,and a comprehensive intelligent early-warning recognition model.The results show that the correct rate of early warning can reach 95.2%.展开更多
With the increase of mining depth, the temperature of the original rock in deep mines increases. High temperature heat hazards at working surfaces and driving faces are becoming increasingly more serious. Given the pr...With the increase of mining depth, the temperature of the original rock in deep mines increases. High temperature heat hazards at working surfaces and driving faces are becoming increasingly more serious. Given the problem of mine cooling technologies at China and abroad and the actual conditions of a coal mine, we developed HEMS （High Temperature Exchange Machinery System） with inrushing mine water as the source of cold energy. Combined with the characteristics of a shortage of inrushing water in the coal mine, we proposed the Sanhejian model of HEMS with its lack of a cold source. The cooling engineer- ing construction, given the present conditions in the Sanhejian Coal Mine, consisted of two phases. In phase 1 horizontal water circulation was used as cold energy, while phase II was the geothermal utiliza- tion project. For the key equipment of HEMS-PT or HEMS-T, we provided the operational principle from theory and an actual application. Finally, we analyzed the operational effect of HEMS. After cooling, the temperature at the working face was below 30 ~C, which meets the national regulations. This system opens up new technology to solve the problem of deep mine heat hazards, which makes good sense in energy conservation and pollution reduction, improves the environment and realizes sustainable eco- nomic development.展开更多
文摘In our study, entropy weight coefficients, based on Shannon entropy, were determined for an attribute recognition model to model the quality of groundwater sources. The model follows the theory previously proposed by Chen Q S. In the model, firstly, the author establishes the attribute space matrix and determines the weight based on Shannon entropy theory; secondly, calculates attribute measure; thirdly, evaluates that with confidence criterion and score criterion; finally, an application example is given. The results show that the water quality of the groundwater sources for the city comes up to the grade II or III standard. There is no pollution that obviously exceeds the standard and the water can meet people’s needs .The results from an evaluation of this model are in basic agreement with the observed situation and with a set pair analysis (SPA) model.
基金financially supported by the National Key Research and Development Program of China(No.2019YFC1805400)。
文摘As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.Due to the many factors affecting water inrush and the complicated water inrush mechanism,many factors close to water inrush may have precursory abnormal changes.At present,the existing monitoring and early warning system mainly uses a few monitoring indicators such as groundwater level,water influx,and temperature,and performs water inrush early warning through the abnormal change of a single factor.However,there are relatively few multi-factor comprehensive early warning identification models.Based on the analysis of the abnormal changes of precursor factors in multiple water inrush cases,11 measurable and effective indicators including groundwater flow field,hydrochemical field and temperature field are proposed.Finally,taking Hengyuan coal mine as an example,6 indicators with long-term monitoring data sequences were selected to establish a single-index hierarchical early-warning recognition model,a multi-factor linear recognition model,and a comprehensive intelligent early-warning recognition model.The results show that the correct rate of early warning can reach 95.2%.
基金Financial support for this project, provided by the Key Basic Research Program of China (No.2006CB202200)the National Major Project of Ministry of Education (No.304005)the Program for Changjiang Scholars and Innovative Research Team in University of China (No.IRT0656)
文摘With the increase of mining depth, the temperature of the original rock in deep mines increases. High temperature heat hazards at working surfaces and driving faces are becoming increasingly more serious. Given the problem of mine cooling technologies at China and abroad and the actual conditions of a coal mine, we developed HEMS （High Temperature Exchange Machinery System） with inrushing mine water as the source of cold energy. Combined with the characteristics of a shortage of inrushing water in the coal mine, we proposed the Sanhejian model of HEMS with its lack of a cold source. The cooling engineer- ing construction, given the present conditions in the Sanhejian Coal Mine, consisted of two phases. In phase 1 horizontal water circulation was used as cold energy, while phase II was the geothermal utiliza- tion project. For the key equipment of HEMS-PT or HEMS-T, we provided the operational principle from theory and an actual application. Finally, we analyzed the operational effect of HEMS. After cooling, the temperature at the working face was below 30 ~C, which meets the national regulations. This system opens up new technology to solve the problem of deep mine heat hazards, which makes good sense in energy conservation and pollution reduction, improves the environment and realizes sustainable eco- nomic development.
