Paper Title:
Gearbox Failure Detection Using Growing Hierarchical Self-Organizing Map
  Abstract

Machine fault diagnosis is essentially an issue of pattern recognition, which heavily depends on suitable unsupervised learning method. The Self-Organizing Map (SOM), a popular unsupervised neural network, has been used for failure detection but with two limitations: needing predefined static architecture and lacking ability for the representation of hierarchical relations in the data. This paper presents a novel study on failure detection of gearbox using the Growing Hierarchical Self-Organizing Map (GHSOM), an artificial neural network model with hierarchical architecture composed of independent growing SOMs. The GHSOM can adapt its architecture during unsupervised training process and provide a global orientation in the individual layers of the hierarchy; hence the original data structure can be described correctly for machine faults diagnosis. Gearbox vibration signals measured under different operating conditions are analyzed using the proposed technique. The results prove that the hierarchical relations in the gearbox failure data can be intuitively represented, and inherent structure can be unfolded. Then gearbox operating conditions including normal, tooth cracked and tooth broken are classified and recognized clearly. The study confirms that GHSOM is very useful and effective for pattern recognition in mechanical fault diagnosis, and provides a good potential for application in practice.

  Info
Periodical
Key Engineering Materials (Volumes 348-349)
Edited by
J. Alfaiate, M.H. Aliabadi, M. Guagliano and L. Susmel
Pages
177-180
DOI
10.4028/www.scientific.net/KEM.348-349.177
Citation
G. L. Liao, T. L. Shi, Z. R. Tang, "Gearbox Failure Detection Using Growing Hierarchical Self-Organizing Map", Key Engineering Materials, Vols. 348-349, pp. 177-180, 2007
Online since
September 2007
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Bong Suk Kim, Soo Hun Lee, Jong Soo Kim, Jun Yeob Song
Abstract:The importance of evaluation and establishment during product development process, for the reliability and safety of mechanical system and...
1535
Authors: Guang Fei Jia, Jian Ping Xuan, Bo Wu, You Min Hu, Yao Cheng
Chapter 4: Applied Mechanics and Other Topics
Abstract:During machining some ultra-intense and special-shaped parts, unstability and surface ablation often turn up. Some large and heavy parts are...
895