Paper Title:
Feature Selection of Acoustic Emission Signal for the Slow-Speed and Heavy-Load Equipment
  Abstract

Selecting feature in slow-speed and heavy-load equipments has always been a difficult problem. A new feature selection method based on Laplacian Score is used to Acoustic Emission signal. The more capable of describing the sample clustering property, the more important the selected feature is. The method is a ‘filter’ and unsupervised feature selection method which is just dependent on the space distribution of the sample instead of classifier. Therefore, the method enjoys a simple algorithm and low complexity. The effectiveness of the method is verified by the AE datasets from the bearings of a blast furnace’s belt conveyor.

  Info
Periodical
Chapter
Chapter 15: Meso/Micro Manufacturing Equipment and Processes
Edited by
Wu Fan
Pages
3199-3203
DOI
10.4028/www.scientific.net/AMM.110-116.3199
Citation
M. Li, J. H. Yang, "Feature Selection of Acoustic Emission Signal for the Slow-Speed and Heavy-Load Equipment", Applied Mechanics and Materials, Vols. 110-116, pp. 3199-3203, 2012
Online since
October 2011
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Price
$32.00
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