Bearing performance degradation assessment based on a combination of empirical mode decomposition and k-medoids clustering
Sign Up to like & getrecommendations! Published in 2017 at "Mechanical Systems and Signal Processing"
DOI: 10.1016/j.ymssp.2017.02.003
Abstract: Abstract Bearing is the most critical component in rotating machinery since it is more susceptible to failure. The monitoring of degradation in bearings becomes of great concern for averting the sudden machinery breakdown. In this… read more here.
Keywords: degradation; bearing performance; medoids clustering; pda ... See more keywords
K-Medoids Clustering of Data Sequences With Composite Distributions
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2019.2901370
Abstract: This paper studies clustering of data sequences using the k-medoids algorithm. All the data sequences are assumed to be generated from unknown continuous distributions, which form clusters with each cluster containing a composite set of… read more here.
Keywords: distance; medoids clustering; distance metric; clustering data ... See more keywords