Jun 13, 2018 · In this paper, we present a new deep feature learning method for RUL estimation approach through time frequency representation (TFR) and ...
In this paper, we present a new deep feature learning method for RUL estimation approach through time frequency representation (TFR) and multi-scale ...
Nov 30, 2018 · Abstract—Bearing remaining useful life (RUL) prediction plays a crucial role in guaranteeing safe operation of ma-.
A multiscale convolutional neural network that merges the final convolutional layers and the final pooling layer was designed to extract the local and global ...
In this paper, an end-to-end remaining useful life prediction method is proposed, which uses short-time Fourier transform (STFT) as preprocessing. Considering ...
Remaining Useful Life Prediction of Rolling Bearings Based on ...
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May 31, 2024 · In this section, the framework of the proposed multiscale. convolutional neural network is introduced in detail. Ma- ; chinery vibration signals ...
Zhu et al. [8] proposed a multiscale convolutional neural network. The last convolutional layer in networks is combined with pooling layer of the previous layer ...
Apr 1, 2019 · Bearing remaining useful life (RUL) prediction plays a crucial role in guaranteeing safe operation of machinery and reducing maintenance ...
Peng, “Estimation of bearing remaining useful life based on multiscale convolutional neural network,” IEEE. Transactions on Industrial Electronics, vol. 66 ...
May 14, 2023 · The remaining useful life (RUL) prediction of rolling bearings based on vibration signals has attracted widespread attention.