Rotating Machinery Fault Diagnosis Under Multiple Working Conditions via a Time-Series Transformer Enhanced by Convolutional Neural Network - researchr publication related

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Zhiqiang Lu, Longyang Liang, Jun Zhu 0012, Wenhao Zou, Lei Mao. Rotating Machinery Fault Diagnosis Under Multiple Working Conditions via a Time-Series Transformer Enhanced by Convolutional Neural Network. IEEE T. Instrumentation and Measurement, 72:1-11, 2023. [doi]

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Multi-Stream Convolutional Neural Networks for Rotating Machinery Fault Diagnosis under Noise and Trend ItemsHan Dong, Jiping Lu, Yafeng Han. sensors, 22(7):2720, 2022. [doi]

An adversarial denoising convolutional neural network for fault diagnosis of rotating machinery under noisy environment and limited sample size caseLei Zou, Yang Li, Feiyun Xu. ijon, 407:105-120, 2020. [doi]

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