首页|Tool Wear State Diagnosis Based on Wavelet Analysis-BP Neural Network

Tool Wear State Diagnosis Based on Wavelet Analysis-BP Neural Network

扫码查看
原文链接
  • NETL
  • NSTL
  • Trans Tech Publications Ltd
Cutting force collected by experiment is transformed by continue wavelet in order to overcome the disadvantage that signal processing analyzes single variable. The eigenvector which can reflect tool wear state is extracted from scale-energy matrix based on analysis, and BP neural network is established to predict tool wear. Trained network is used for prediction by unknown sample. Results show that this method can identify and diagnose accurately tool wear state.

cutting forcetool wearwavelet analysisBP neural networkfailure diagnosis

Ning Fan、Hang Liang、Peiquan Guo

展开 >

School of Mechanical Engineering, University of Jinan, Jinan, China, 250022

2010

10.4028/www.scientific.net/KEM.431-432.253

Key engineering materials

Key engineering materials

ISSN：1013-9826
年,卷(期)：2010.431/432
  • 1
  • 6