DocumentCode :
3778237
Title :
Flatness detection research based on the string vibration method
Author :
Jia Meng; Li Qi; Liang Yanming
Author_Institution :
Automation and Information Engineering, Xi´an University of Technology, 710054, china
Volume :
3
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
1587
Lastpage :
1592
Abstract :
In order to better identify the flatness pattern, this paper proposes a non-contacted flatness detection called string vibration method. This method first use the principle of string vibration to design the detection scheme, and then use the wavelet packet decomposition to extract the effective shape characteristics, finally use the RBF neural network with strong classification ability to come true the shape pattern classification. By building shape detection platform, getting a lot of experimental data, the relationship between wavelet node vector and shape pattern was established. The plate-shaped pattern recognition rate reached 90%. The method improves the shortcomings of FFT in vibration signal feature extraction, the idea of string vibration method provides a new solution for the flatness detection.
Keywords :
"Feature extraction","Wavelet analysis","Vibration measurement","Wavelet packets","Vibrations","Gold","Eigenvalues and eigenfunctions"
Publisher :
ieee
Conference_Titel :
Electronic Measurement & Instruments (ICEMI), 2015 12th IEEE International Conference on
Type :
conf
DOI :
10.1109/ICEMI.2015.7494481
Filename :
7494481
Link To Document :
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