Failure depth of coal seam floors is one of the important considerations that must be kept in mind when mining is carried out above a confined aquifer. In order to study the factors that affect the failure depth of co...Failure depth of coal seam floors is one of the important considerations that must be kept in mind when mining is carried out above a confined aquifer. In order to study the factors that affect the failure depth of coal seam floors such as mining depth, coal seam pitch, mining thickness, workface length and faults, we propose a combined artificial neural networks (ANN) prediction model for failure depth of coal seam floors on the basis of existing engineering data by using genetic algorithms to train the ANN. A practical engineering application at the Taoyuan Coal Mine indicates that this method can effectively determine the network struc- ture and training parameters, with the predicted results agreeing with practical measurements. Therefore, this method can be applied to relevant engineering projects with satisfactory results.展开更多
This article describes the development of automatic control system on the basis of Festo ＂Compact Workstation＂ training stand. Such control systems are used in different branches of industry and infrastructure inclu...This article describes the development of automatic control system on the basis of Festo ＂Compact Workstation＂ training stand. Such control systems are used in different branches of industry and infrastructure including oil industry, chemical industry, water treatment, canalization and others. The stand allows realizing level, flow, pressure and temperature control systems, using pump, valves, discrete and analog sensors. Level control system is described in this work. PID （proportional integral derivative） controllers are used in these systems. Control is switched on and off and the parameters of control systems are changed by means of SCADA （supervisory control and data acquisition） system. During real technological processes, these actions are performed by the operator. The algorithm of the control system is realized using PLC （programmable logic controller）. At the end of the article conclusions about the research are drawn.展开更多
基金Projects 50874103 supported by the National Natural Science Foundation of China2006CB202210 by the National Basic Research Program of China+1 种基金BK2008135 by the Natural Science Foundation of Jiangsu Provincethe Qing-lan Project of Jiangsu Province
文摘Failure depth of coal seam floors is one of the important considerations that must be kept in mind when mining is carried out above a confined aquifer. In order to study the factors that affect the failure depth of coal seam floors such as mining depth, coal seam pitch, mining thickness, workface length and faults, we propose a combined artificial neural networks (ANN) prediction model for failure depth of coal seam floors on the basis of existing engineering data by using genetic algorithms to train the ANN. A practical engineering application at the Taoyuan Coal Mine indicates that this method can effectively determine the network struc- ture and training parameters, with the predicted results agreeing with practical measurements. Therefore, this method can be applied to relevant engineering projects with satisfactory results.
文摘This article describes the development of automatic control system on the basis of Festo ＂Compact Workstation＂ training stand. Such control systems are used in different branches of industry and infrastructure including oil industry, chemical industry, water treatment, canalization and others. The stand allows realizing level, flow, pressure and temperature control systems, using pump, valves, discrete and analog sensors. Level control system is described in this work. PID （proportional integral derivative） controllers are used in these systems. Control is switched on and off and the parameters of control systems are changed by means of SCADA （supervisory control and data acquisition） system. During real technological processes, these actions are performed by the operator. The algorithm of the control system is realized using PLC （programmable logic controller）. At the end of the article conclusions about the research are drawn.
