Abstract
An optimized recurrent neural network fault diagnosis model for the failure of the massage chair movement is proposed in this paper. An optimized Attention-RNN-MLP, Attention-LSTM-MLP and Attention-GRU-MLP fault diagnosis models are constructed by adding the Attention mechanism and MLP network to RNN, LSTM and GRU. The Attention-GRU-MLP fault diagnosis model is proved to be more rational by comparing the differences among these 3 models.
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Lu, L., Cai, X., Li, G., Mitrouchev, P. (2022). Fault Diagnosis of Massage Chair Movement Based on Attention-GRU-MLP. In: Wang, Y., Martinsen, K., Yu, T., Wang, K. (eds) Advanced Manufacturing and Automation XI. IWAMA 2021. Lecture Notes in Electrical Engineering, vol 880. Springer, Singapore. https://doi.org/10.1007/978-981-19-0572-8_8
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DOI: https://doi.org/10.1007/978-981-19-0572-8_8
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