The Diagnosis of Forging Bevel Gears on the Information Merge of Wavelet Neural Network

DOI

10.2991/jimec-16.2016.74How to use a DOI?

Keywords

wavelet neural network; bevel gear ;defect; information merge ;

Abstract

The synthetical symptoms of bevel gear is concluded. Using wavelet and mixed data merge does the intelligence diagnosis to the defect of bevel gear , which is integrated with data , characteristic, decision grate and nerve network . A model of wavelet neural network is constructed. In order to reduce no confirm of defect analysis , the excellent diagnosis way is studied with the information of many sources fill and redundant. The result is given that using mixed data merge may raise tolerate character with the help of many sources fill and redundant,and using wavelet and mixed data merge does the effective diagnosis of bevel gear.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhanjun Liu
PY  - 2016/10
DA  - 2016/10
TI  - The Diagnosis of Forging Bevel Gears on the Information Merge of Wavelet Neural Network
BT  - Proceedings of the 2016 Joint International Information Technology, Mechanical and Electronic Engineering
PB  - Atlantis Press
SP  - 412
EP  - 415
SN  - 2352-5401
UR  - https://doi.org/10.2991/jimec-16.2016.74
DO  - 10.2991/jimec-16.2016.74
ID  - Liu2016/10
ER  -