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APPLICATION OF THE UNSUPERVISED NEURAL NETWORK FOR DIAGONOSING FAULTS IN A SPUR GEAR SYSTEM

Tung Thanh Luu 1, *
  1. University of Technology, VNU -HCM
Correspondence to: Tung Thanh Luu, University of Technology, VNU -HCM. Email: pvphuc@hcmuns.edu.vn.
Volume & Issue: Vol. 12 No. 8 (2009) | Page No.: 29-37 | DOI: 10.32508/stdj.v12i8.2272
Published: 2009-04-28

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Copyright The Author(s) 2023. This article is published with open access by Vietnam National University, Ho Chi Minh city, Vietnam. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0) which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. 

Abstract

In transmission, gearbox with normal teeth is used popularly. Now, fault detection of gearbox is made by listening to abnormal noise and opening the gearbox to find the fault. This work takes much time and labour and results are not always exact. In this paper, vibration signal caused by fault are recorded and transformed into spectrum. The spectrum is used to train the unsupervised neural network. After the traning is completed, the unsupervised neural network will recognize the kind of fault which is produced by gearbox. Results of recognition from this method are almost exact when compared with others.

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