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

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

Internet

https://ieeexplore.ieee.org/document/9353541/

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