Features Linear Fusion Based on AP Clustering and AASC Algorithm

Li Min Li; Zhong Sheng Wang

doi:10.4028/www.scientific.net/AMM.483.583

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 483Features Linear Fusion Based on AP Clustering and...

Features Linear Fusion Based on AP Clustering and AASC Algorithm

Abstract:

In the field of mechanical fault diagnosis, in order to improve the diagnosis accuracy with high feature dimension, a method of features linear fusion method based on AP(Affinity propagation clustering) and AASC(Affinity Aggregation for Spectral Clustering) algorithm was proposed. Low dimension space was obtained by AP clustering, then using AASC algorithm to fuse this selected features, and gained a new feature, meanwhile which can be used independently as a new feature. In the phase of experiment, this method was compared with respectively LPP and PCA, it’s result indicates that this method is excellent in improving diagnosis accuracy.

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Periodical:

Applied Mechanics and Materials (Volume 483)

Pages:

583-586

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.483.583

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Online since:

December 2013

Authors:

Li Min Li*, Zhong Sheng Wang

Keywords:

AASC Algorithm, Affinity Propagation Clustering, Features Linear Fusion

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* - Corresponding Author

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