Rotor fault diagnosis using a convolutional neural network with symmetrized dot pattern images

Xiaoxun Zhu(North China Electric Power University), Qianqian Yin(North China Electric Power University), Zhonghe Han(North China Electric Power University), Yiming Yuan(North China Electric Power University), Dongnan Hou(North China Electric Power University), Weiwei Zhou(North China Electric Power University), Pei Zhou(North China Electric Power University)
Measurement
February 13, 2019
10.1016/j.measurement.2019.02.022
Cited by 111

Related Papers

Accuracy analyses and model comparison of machine learning adopted in building energy consumption prediction
|Energy Exploration & Exploitation|2019|157
Effect of Li doping on structure and superconducting transition temperature of Mg1−xLixB2
|Physica C Superconductivity|2001|90
Thermodynamic analyses and optimization of a novel CCHP system integrated organic Rankine cycle and solar thermal utilization
|Energy Conversion and Management|2019|90
Comparative study of optimization method and optimal operation strategy for multi-scenario integrated energy system
|Energy|2020|89
Scientific and technological progress and future perspectives of the solar assisted heat pump (SAHP) system
|Energy|2021|88