Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Remaining Useful Life Prediction Using Temporal Deep Degradation Network
  for Complex Machinery with Attention-based Feature Extraction   The precise estimate of remaining useful life (RUL) is vital for the
prognostic analysis and predictive maintenance that can significantly reduce
failure rate and maintenance costs. The degradation-related features extracted
from the sensor streaming data with neural networks can dramatically improve
the accuracy of the RUL prediction. The Temporal deep degradation network
(TDDN) model is proposed to make the RUL prediction with the
degradation-related features given by the one-dimensional convolutional neural
network (1D CNN) feature extraction and attention mechanism. 1D CNN is used to
extract the temporal features from the streaming sensor data. Temporal features
have monotonic degradation trends from the fluctuating raw sensor streaming
data. Attention mechanism can improve the RUL prediction performance by
capturing the fault characteristics and the degradation development with the
attention weights. The performance of the TDDN model is evaluated on the public
C-MAPSS dataset and compared with the existing methods. The results show that
the TDDN model can achieve the best RUL prediction accuracy in complex
conditions compared to current machine learning models. The degradation-related
features extracted from the high-dimension sensor streaming data demonstrate
the clear degradation trajectories and degradation stages that enable TDDN to
predict the turbofan-engine RUL accurately and efficiently.

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The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
6
The categories of this paper are: astro-ph
5
The categories of this paper are: gr-qc
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
9
The categories of this paper are: nlin
32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
35
The categories of this paper are: mtrl-th
3
The categories of this paper are: physics
12
The categories of this paper are: nucl-th
33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
10
The categories of this paper are: q-bio