DocumentCode
554445
Title
Research on the milling tool monitoring system based on wavelet neural network
Author
Guizhong Guo ; Xinhua Mao
Author_Institution
Xinxiang Univ., Xinxiang, China
Volume
3
fYear
2011
fDate
12-14 Aug. 2011
Firstpage
1421
Lastpage
1423
Abstract
Among the milling process, the signal representation tools sharply wearing in primary stage, is weaker. While the work piece accuracy have already at this time obvious change. Wavelet neural network can effectively handle various signals with different frequency, but it is possible that it can not detect the faint signal. Based on monitoring accuracy change of the workpiece, do modify the parameter of wavelet transform in time, and it can enhance the ability of monitoring faint signal, decrease missing rate and false alarm rate.
Keywords
computerised monitoring; milling machines; neural nets; signal detection; signal representation; wavelet transforms; faint signal detection; false alarm rate; milling tool monitoring system; signal representation tools; wavelet neural network; wavelet transform; Accuracy; Biological neural networks; Force; Milling; Monitoring; Surface roughness; Wavelet transforms; Monitoring; The milling Cutter; Wavelet neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location
Harbin, Heilongjiang, China
Print_ISBN
978-1-61284-087-1
Type
conf
DOI
10.1109/EMEIT.2011.6023313
Filename
6023313
Link To Document