Isomap and Deep Belief Network-Based Machine Health Combined Assessment Model

@article{Yin2016IsomapAD,
  title={Isomap and Deep Belief Network-Based Machine Health Combined Assessment Model},
  author={Aijun Yin and Juncheng Lu and Zongxian Dai and Jiang Li and Qi Ouyang},
  journal={Strojniski Vestnik-journal of Mechanical Engineering},
  year={2016},
  volume={62},
  pages={740-750}
}
This paper presents a novel combined assessment model (CAM) for machine health assessment, in which 38 original features of the vibration signal were extracted from time domain analysis, frequency domain analysis, and wavelet packet transform (WPT), following which the nonlinear global algorithm Isomap was adopted for dimensionality reduction and extraction of the more representative features. Next, the acquired low-dimensional features array is input into the well trained deep belief… 

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