Gateway floor heave control is the key to guarantee mine safe and efficient production. Through analysis of floor instability characteristics and bolting control, gateway floor strata show second level stress under ab...Gateway floor heave control is the key to guarantee mine safe and efficient production. Through analysis of floor instability characteristics and bolting control, gateway floor strata show second level stress under abutment pressure, which causes plastic flow failure in floor strata; gateway floor instability shows mainly shear-break slippage of ＂triangle sliding body＂. Mechanics of floor bolting is mainly a function of connection and combination. Main area of bolting control lies in two gateway floor angles. The paper analyzes mechanics principle of gateway floor instability, constructs stability mechanics model of gateway floor bolting, obtains gateway floor stability criterion of different bolting angles and optimum formula of bolting parameters, carries out the engineering example, and guides better field application. It provides theoretical base for bolting gateway floor instability control.展开更多
Flatness pattern recognition is the key of the flatness control. The accuracy of the present flatness pattern recognition is limited and the shape defects cannot be reflected intuitively. In order to improve it, a nov...Flatness pattern recognition is the key of the flatness control. The accuracy of the present flatness pattern recognition is limited and the shape defects cannot be reflected intuitively. In order to improve it, a novel method via T-S cloud inference network optimized by genetic algorithm(GA) is proposed. T-S cloud inference network is constructed with T-S fuzzy neural network and the cloud model. So, the rapid of fuzzy logic and the uncertainty of cloud model for processing data are both taken into account. What's more, GA possesses good parallel design structure and global optimization characteristics. Compared with the simulation recognition results of traditional BP Algorithm, GA is more accurate and effective. Moreover, virtual reality technology is introduced into the field of shape control by Lab VIEW, MATLAB mixed programming. And virtual flatness pattern recognition interface is designed.Therefore, the data of engineering analysis and the actual model are combined with each other, and the shape defects could be seen more lively and intuitively.展开更多
基金Supported by the National Natural Science Foundation of China （50874037）
文摘Gateway floor heave control is the key to guarantee mine safe and efficient production. Through analysis of floor instability characteristics and bolting control, gateway floor strata show second level stress under abutment pressure, which causes plastic flow failure in floor strata; gateway floor instability shows mainly shear-break slippage of ＂triangle sliding body＂. Mechanics of floor bolting is mainly a function of connection and combination. Main area of bolting control lies in two gateway floor angles. The paper analyzes mechanics principle of gateway floor instability, constructs stability mechanics model of gateway floor bolting, obtains gateway floor stability criterion of different bolting angles and optimum formula of bolting parameters, carries out the engineering example, and guides better field application. It provides theoretical base for bolting gateway floor instability control.
基金Project(LJRC013)supported by the University Innovation Team of Hebei Province Leading Talent Cultivation,China
文摘Flatness pattern recognition is the key of the flatness control. The accuracy of the present flatness pattern recognition is limited and the shape defects cannot be reflected intuitively. In order to improve it, a novel method via T-S cloud inference network optimized by genetic algorithm(GA) is proposed. T-S cloud inference network is constructed with T-S fuzzy neural network and the cloud model. So, the rapid of fuzzy logic and the uncertainty of cloud model for processing data are both taken into account. What's more, GA possesses good parallel design structure and global optimization characteristics. Compared with the simulation recognition results of traditional BP Algorithm, GA is more accurate and effective. Moreover, virtual reality technology is introduced into the field of shape control by Lab VIEW, MATLAB mixed programming. And virtual flatness pattern recognition interface is designed.Therefore, the data of engineering analysis and the actual model are combined with each other, and the shape defects could be seen more lively and intuitively.
