Multichannel one-dimensional convolutional neural network-based feature learning for fault diagnosis of industrial processes - researchr publication related

researchr

You are not signed in
Sign in
Sign up

Jianbo Yu, Chengyi Zhang, Shijin Wang. Multichannel one-dimensional convolutional neural network-based feature learning for fault diagnosis of industrial processes. Neural Computing and Applications, 33(8):3085-3104, 2021. [doi]

The following publications are possibly variants of this publication:

Sparse one-dimensional convolutional neural network-based feature learning for fault detection and diagnosis in multivariable manufacturing processesJianbo Yu, Chengyi Zhang, Shijin Wang 0002. nca, 34(6):4343-4366, 2022. [doi]

Fault detection and recognition of multivariate process based on feature learning of one-dimensional convolutional neural network and stacked denoised autoencoderChengyi Zhang, Jianbo Yu, Shijin Wang 0002. ijpr, 59(8):2426-2449, 2021. [doi]

Broad Convolutional Neural Network Based Industrial Process Fault Diagnosis With Incremental Learning CapabilityWanke Yu, Chunhui Zhao. tie, 67(6):5081-5091, 2020. [doi]

One-Dimensional Residual Convolutional Autoencoder Based Feature Learning for Gearbox Fault DiagnosisJianbo Yu, Xingkang Zhou. tii, 16(10):6347-6358, 2020. [doi]

Fault diagnosis of multi-unit nonlinear industrial processes based on a global-local attention convolutional neural networkXueqin Yang, Yun Wang, Lijuan Qian, Gangyue Ye, Weirong Ye, Yuchen He. eaai, 159:111747, 2025. [doi]

runs on WebDSL