Papers by Author: L.B. Zhang

Paper TitlePage

Authors: Jian Ruan, Qing Feng Wang, L.B. Zhang, Ju Long Yuan, Q.H. Yang
706
Authors: Shi Ming Ji, L.B. Zhang, Y.H. Wan, Ju Long Yuan, Li Zhang, X. Zhang, S.C. Xiong, Q.H. Yang
761
Authors: Jin Long Yang, Jian Ruan, Ju Long Yuan, L.B. Zhang
459
Authors: X. Shen, M. Chang, Ju Long Yuan, Ping Zhao, Wen Hong Zhao, L.B. Zhang
466
Authors: J. Dong, Wei Wang, Shi Ming Ji, L.B. Zhang
Abstract: A single-chip silicon condenser microphone with a sandwich diaphragm and an electroplating perforated copper backplate has been developed. The sandwich diaphragm is designed to have a slight tensile stress. The backplate is made using copper electroplating technology and perforated with circular holes. Perforated circular holes on backplate are laid out as hexagon to adjust air-gap damping between diaphragm and backplate to critical damping to enlarge frequency bandwidth of microphone. Fabrication is simple enough and only needs five photolithography marsks. Measurements show the open-circuit with 9V bias voltage reaches 5.45mv/Pa in 1KHz, pull-in voltage is 14V, and the flat frequency response within 3Db is from 100Hz to 20KHz. The performances of microphone meet the requirement of industrial use. Thereby, it has promising prospect for industrial and commercial field.
565
Authors: Li Zhang, Shi Ming Ji, L.B. Zhang, J.B. Shen, Ju Long Yuan
730
Authors: Ju Long Yuan, Bin Lin, Z.W. Shen, Jia Jin Zheng, Jian Ruan, L.B. Zhang
85
Authors: Shi Ming Ji, Li Zhang, Y.H. Wan, X. Zhang, Ju Long Yuan, L.B. Zhang
Abstract: The Mahalanobis distance feature proposed by P.C .Mahalanobis, an indian statistician. In this paper, we propose a new concept, Local Region Mahalanobis Distance feature –LRMD feature, we shall discuss the structure form, the obtaining methods of LRMD feature from an image and the relations between the LRMD feature and wearing and breakage states of cutting tools. The new research results indicate that the method of automatic on-line cutting tool condition monitoring based on LRMD feature can has better inspect result than the method of Mahalanobis Distance feature.
418
Authors: Ju Long Yuan, Bin Lin, Z.W. Shen, Jia Jin Zheng, Jian Ruan, L.B. Zhang
235
Authors: Shi Ming Ji, Li Zhang, Y.H. Wan, X. Zhang, Ju Long Yuan, L.B. Zhang
Abstract: A new intelligent tool condition monitoring technique for metal cutting process is proposed. Fiest, the frequency spectrum analysis of the audio signal during cutting process, the pixel space projection analysis and equal gray pace analysis of the images of machined workpiece surface are introduced. Then combined the results of the audio signal analysis and the workpiece surface image analysis with artificial neural network, we implemented the intelligent tool condition monitoring based on multi-information fusion. The experimental results indicate that this method can recognize the tool condition effectively and improve the dependability of tool condition monitoring.
187
Showing 1 to 10 of 16 Paper Titles