Intelligent fault diagnosis of rolling bearings based on normalized CNN considering data imbalance and variable working conditions

Bo Zhao; Xianmin Zhang; Hai Li; Zhuobo Yang

doi:10.1016/j.knosys.2020.105971

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JOURNAL ARTICLE

Intelligent fault diagnosis of rolling bearings based on normalized CNN considering data imbalance and variable working conditions

Bo Zhao Xianmin Zhang Hai Li Zhuobo Yang

Year: 2020 Journal: Knowledge-Based Systems Vol: 199 Pages: 105971-105971 Publisher: Elsevier BV

DOI: 10.1016/j.knosys.2020.105971

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Keywords:

Robustness (evolution) Computer science Fault (geology) Normalization (sociology) Artificial intelligence Convolutional neural network Generalization Stability (learning theory) Artificial neural network Pattern recognition (psychology) Data mining Machine learning Mathematics

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Topics

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

Intelligent fault diagnosis of rolling bearings based on normalized CNN considering data imbalance and variable working conditions

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Citation History

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