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《China Mechanical Engineering》 2016-02
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Shearer's Coal-rock Recognition System Based on Fuzzy Neural Network Information Fusion

Zhang Qiang;Wang Haijian;Jing Wang;Mao Jun;Yuan Zhi;Hu Denggao;Liaoning Technical University;State Key Laboratory of Structural Analysis for Industrial Equipment,Dalian University of Technology;Material Corrosion and Protection Key Laboratory of Sichuan Province,Sichuan University of Science & Engineering;China National Coal Mining Equipment Co.,Ltd.;  
Aiming at the low accuracy and reliability problems when using single signals to recognize the coal-rock interface for controlling and adjusting the height of shearer roller,a multi-sensor information fusion coal-rock recognition method was put forward based on fuzzy neural network.The sample characteristics of vibration,current and sound power spectrum signals were obtained through the acquisition and analyses of experimental data during cutting the section with different proportions of coal-rock,and the coal-rock recognition signals' fuzzy membership function was found according to the minimum fuzzy optimization model.The controlled measurement of roller's height with highly reliability and accuracy was obtained through multi-dimensional fuzzy neural network,which was built by adaptive neuro-fuzzy inference system.Laboratory cutting experiments and the scene cutting experiments of random coal-rock trajectory were carried out,the results show that the cutting trajectory of shearer's roller is basically the same as the random trajectory of coal-rock specimen,the results confirm the effectiveness and reliability of the system.
【Fund】: 高等学校博士学科点专项科研基金资助项目(20132121120011);; 工业装备结构分析国家重点实验室开放基金资助项目(GZ1402);; 材料腐蚀与防护四川省重点实验室开放基金资助项目(2014CL18);; 辽宁省高等学校杰出青年学者成长计划资助项目(LJQ2014036);; 辽宁“百千万人才工程”培养经费资助项目(2014921070);; 中煤集团重点科技项目(13-8)
【CateGory Index】: TD632.1;TP183
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