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Xigeng Song
Researcher at Dalian University of Technology
Publications - 4
Citations - 192
Xigeng Song is an academic researcher from Dalian University of Technology. The author has contributed to research in topics: Support vector machine & Bearing (mechanical). The author has an hindex of 4, co-authored 4 publications receiving 171 citations.
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A roller bearing fault diagnosis method based on hierarchical entropy and support vector machine with particle swarm optimization algorithm
TL;DR: The experimental results indicate that HE can depict the characteristics of the bearing vibration signal more accurately and more completely than MSE, and the proposed approach based on HE can identify various bearing conditions effectively and accurately and is superior to that based on MSE.
Journal Article
Incipient fault diagnosis of roller bearings using empirical mode decomposition and correlation coefficient
TL;DR: In this article, an early fault diagnosis method for roller bearings is proposed, based on empirical mode decomposition (EMD) and correlation coefficient (the normalized value of the cross-correlation function at the zero-lag point).
Journal ArticleDOI
Fault Diagnosis of Rolling Bearings Based on IMF Envelope Sample Entropy and Support Vector Machine
TL;DR: The experimental results indicate that the proposed approach based on IMF envelope SampEn can identify different fault types as well as levels of severity effectively and is superior to thatbased on IMF SampEn.
Journal ArticleDOI
Cross-fuzzy entropy-based approach for performance degradation assessment of rolling element bearings:
Keheng Zhu,Xigeng Song +1 more
TL;DR: The modified cross-fuzzy entropy is introduced and is used to measure the similarity of patterns between normal signals and tested signals of the rolling element bearings, and the degree of similarity is used as an indicator of the bearing performance degradation.