Li Guo, doctor, doctoral supervisor, master supervisor, professor of School of Mechanical and Vehicle Engineering, Hunan University, academic backbone of Hunan University, senior member of China Society of Mechanical Engineering, judge of Ministry of Science and Technology, evaluation expert of National Natural Science Foundation, evaluation expert of China Institute of Science and Technology Information, Ministry of Science and Technology, Evaluation experts of science and technology projects and science and technology awards of the Ministry of Science and Technology and the Ministry of Education, evaluation experts of science and technology awards of 8 provinces including Hunan, Shandong and Zhejiang, evaluation experts of Natural science Foundation of 8 provinces including Hunan, Zhejiang and Shandong, academic backbone of National High Efficiency Grinding Engineering and Technology Research Center,National 985 High Technology Research (Automotive Advanced design and manufacturing innovation team) academic backbone.He is an excellent reviewer of Chinese science and technology papers, editorial board member of national Chinese core science and technology journals Precision Manufacturing and Automation and Electromechanical Engineering.Evaluation expert of International Journal of Advanced Manufacturing Technology, reviewer of national first-class scientific and technological journals Journal of Vibration Engineering, Journal of Hunan University and Engineering Mechanics.Research field: Intelligent and efficient precision grinding technology and CNC machine tools;Intelligent machine tool dynamic and static spindle system;Advanced automobile design and manufacture and body welding and stamping technology;Intelligent opto-mechatronics design and manufacture.

Speech Title: Research on acoustic emission intelligent monitoring in grinding engineering ceramics

Abstract: Acoustic emission (AE) signal analysis by use of short time Fourier transform is used to monitor the grinding heat by ues of laser. The relationship between the acoustic emission signal of high speed grinding of engineering ceramics and grinding force, grinding temperature are studied. High precision AE monitoring of diamond grinding wheel wear in engineering ceramics grinding were carried out. The variance of wavelet decomposition coefficient of AE signal in alumina grinding is used as the input feature of support vector machine. The empirical mode decomposition (EMD) of grinding AE signal is used to extract the effective value, variance and energy coefficient of its intrinsic mode function as the input features of least squares support vector machine. The optimized BP neural network is used to monitor the grinding surface roughness with high precision by use of AE. The research solved the problem of acoustic emission monitoring in engineering ceramics grinding!