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西北工业大学 国内
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Hierarchical fuzzy entropy and improved support vector machine based binary tree approach for rolling bearing fault diagnosis
Yongbo Li
, Minqiang Xu, Haiyang Zhao, Wenhu Huang
Harbin Institute of Technology
科研成果
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期刊稿件
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同行评审
86
引用 (Scopus)
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探究 'Hierarchical fuzzy entropy and improved support vector machine based binary tree approach for rolling bearing fault diagnosis' 的科研主题。它们共同构成独一无二的指纹。
分类
加权
按字母排序
Engineering
Bearing Fault Diagnosis
100%
Binary Tree
100%
Entropy Method
100%
Experimental Result
33%
Feature Extraction
33%
High-Frequency Component
33%
Laplace Operator
66%
Multiscale
33%
Rolling Bearings
100%
Scale Factor
33%
Support Vector Machine
100%
Computer Science
Binary Tree
100%
Experimental Result
33%
fault diagnose method
33%
Fault Diagnosis
100%
Feature Extraction
33%
Frequency Component
33%
Hierarchical Method
33%
Laplacian Score
66%
Operating Condition
33%
Pattern Identification
33%
Support Vector Machine
100%
vibration signal
66%
Chemical Engineering
Support Vector Machine
100%