Prognosis of Defect Propagation Based on Recurrent Neural Networks

@article{Malhi2011PrognosisOD,
  title={Prognosis of Defect Propagation Based on Recurrent Neural Networks},
  author={Arnaz Malhi and Ruqiang Yan and Robert X. Gao},
  journal={IEEE Transactions on Instrumentation and Measurement},
  year={2011},
  volume={60},
  pages={703-711}
}
Incremental training is commonly applied to training recurrent neural networks (RNNs) for applications involving prognosis. As the number of prognostic time-step increases, the accuracy of prognosis generally decreases, as often seen in long-term prognosis. Revision of the training techniques is therefore necessary to improve the accuracy in long-term prognosis. This paper presents a competitive learning-based approach to long-term prognosis of machine health status. Specifically, vibration… CONTINUE READING

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