Bearing performance degradation assessment based on a combination of empirical mode decomposition and k-medoids clustering

Akhand Rai; Sanjay Upadhyay

doi:10.1016/j.ymssp.2017.02.003

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Bearing performance degradation assessment based on a combination of empirical mode decomposition and k-medoids clustering

Akhand Rai Sanjay Upadhyay

Year: 2017 Journal: Mechanical Systems and Signal Processing Vol: 93 Pages: 16-29 Publisher: Elsevier BV

DOI: 10.1016/j.ymssp.2017.02.003

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Keywords:

Bearing (navigation) Cluster analysis Hilbert–Huang transform Pattern recognition (psychology) Computer science Fault (geology) Artificial intelligence Data mining Fuzzy clustering Time domain Frequency domain Engineering Computer vision

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Machine Fault Diagnosis Techniques

Physical Sciences → Engineering → Control and Systems Engineering

Gear and Bearing Dynamics Analysis

Physical Sciences → Engineering → Mechanical Engineering

Mechanical Failure Analysis and Simulation

Physical Sciences → Engineering → Mechanical Engineering

Bearing performance degradation assessment based on a combination of empirical mode decomposition and k-medoids clustering

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