Convolutional neural network framework to predict remaining useful life in machines

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Modern industries require efficient and reliable machinery. To ensure the stability of industrial equipment and avoid unnecessary downtime, it is important to gauge a machine's remaining useful life (RUL) accurately. This has been done using deep learning-based approaches. In particular, deep neural networks are considered promising in this regard.
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