A Novel Bearing Fault Diagnosis Method Using Spark-Based Parallel ACO-K-Means Clustering Algorithm

K-Means clustering algorithm is a typical unsupervised learning method, and it has been widely used in the field of fault diagnosis. However, the traditional serial K-Means clustering algorithm is difficult to efficiently and accurately perform clustering analysis on the massive running-state monito...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Lanjun Wan, Gen Zhang, Hongyang Li, Changyun Li
Format:	Article
Language:	English
Published:	IEEE 2021-01-01
Subjects:	Ant colony optimization fault diagnosis K-Means clustering rolling bearing spark wavelet packet decomposition
Online Access:	https://ieeexplore.ieee.org/document/9353541/