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Fault detection and diagnosis for reactive distillation based on convolutional neural network
Computers & Chemical Engineering
◽
10.1016/j.compchemeng.2020.107172
◽
2021
◽
Vol 145
◽
pp. 107172
Author(s):
Xiaolong Ge
◽
Beibei Wang
◽
Xinchuang Yang
◽
Yu Pan
◽
Botan Liu
◽
...
Keyword(s):
Neural Network
◽
Fault Detection
◽
Convolutional Neural Network
◽
Reactive Distillation
◽
Fault Detection And Diagnosis
◽
Detection And Diagnosis
Download Full-text
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Multiple time-series convolutional neural network for fault detection and diagnosis and empirical study in semiconductor manufacturing
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Deep Convolutional Neural Network with Deconvolution and a Deep Autoencoder for Fault Detection and Diagnosis
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◽
10.1021/acsomega.1c06607
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◽
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Fault Detection and Diagnosis of Chillers with S&D Convolutional Neural Network
2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)
◽
10.1109/ithings-greencom-cpscom-smartdata-cybermatics50389.2020.00141
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2020
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Xueteng Sun
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Model-based Fault Detection and Diagnosis for HVAC Systems Using Convolutional Neural Network
Proceedings of Building Simulation 2019: 16th Conference of IBPSA
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10.26868/25222708.2019.210311
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Sparse one-dimensional convolutional neural network-based feature learning for fault detection and diagnosis in multivariable manufacturing processes
Neural Computing and Applications
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Jianbo Yu
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Wind turbine fault detection and diagnosis using LSTM neural network
2020 39th Chinese Control Conference (CCC)
◽
10.23919/ccc50068.2020.9188709
◽
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◽
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A hybrid neural network model for rule generation and its application to process fault detection and diagnosis
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Fault Detection and Diagnosis with A Novel Source-Aware Autoencoder and Deep Residual Neural Network
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