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A novel scalable method for machine degradation assessment using deep convolutional neural network

  • Published:2020-02 Issue: Volume:151 Page:107106
  • ISSN:0263-2241
  • Container-title:Measurement
  • language:en
  • Short-container-title:Measurement

Author:

Li Pin,Jia Xiaodong,Feng Jianshe,Zhu Feng,Miller Marcella,Chen Liang-Yu,Lee Jay

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference30 articles.

1. Assessment of data suitability for machine prognosis using maximum mean discrepancy;Jia;IEEE Trans. Ind. Electron.,2018

2. A deviation based assessment methodology for multiple machine health patterns classification and fault detection;Jia;Mech. Syst. Signal Process.,2018

3. Real-time estimation of mean remaining life using sensor-based degradation models;Elwany;J. Manuf. Sci. Eng.,2009

4. An auto-associative residual processing and K-means clustering approach for anemometer health assessment;Siegel;Int. J. Progn. Heal. Manag.,2011

5. A novel method for deposit accumulation assessment in dry etching chamber;Li;IEEE Trans. Semicond. Manuf.,2019

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