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西北工业大学 国内
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Improved Variational Mode Decomposition and CNN for Intelligent Rotating Machinery Fault Diagnosis
Qiyang Xiao, Sen Li, Lin Zhou,
Wentao Shi
海洋研究院
Henan University
科研成果
:
期刊稿件
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同行评审
24
引用 （Scopus）
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探究 'Improved Variational Mode Decomposition and CNN for Intelligent Rotating Machinery Fault Diagnosis' 的科研主题。它们共同构成独一无二的指纹。
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Computer Science
Convolutional Neural Network
100%
Machinery Fault Diagnosis
100%
Feature Extraction
66%
Domain Feature
66%
Neural Network
33%
Wavelet Transform
33%
Deep Learning Method
33%
Complex Environment
33%
Fault Diagnosis
33%
Feature Map
33%
Recognition Rate
33%
Frequency Domain
33%
Decomposition Method
33%
Signal Component
33%
Image Frequency
33%
Subjective Experience
33%
Nonstationary Signal
33%
Engineering
Fault Diagnosis
100%
Rotating Machinery
100%
Convolutional Neural Network
100%
Variational Mode Decomposition
100%
Two Dimensional
50%
Feature Extraction
50%
Domain Feature
50%
Time Domain
25%
Frequency Domain
25%
Deep Learning Method
25%
Recognition Rate
25%
Signal Component
25%
Image Frequency
25%
Subjective Experience
25%
Chemical Engineering
Neural Network
100%
Deep Learning Method
50%