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A novel deep quality-supervised regularized autoencoder model for quality-relevant fault detection

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Acknowledgements

This work was supported by National Key Research and Development Program of China (Grant No. 2020YFA0908303) and National Natural Science Foundation of China (Grant No. 21878081).

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Authors and Affiliations

  1. Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China

    Zhichao Li, Li Tian & Xuefeng Yan

Authors
  1. Zhichao Li
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  2. Li Tian
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  3. Xuefeng Yan
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Corresponding author

Correspondence to Xuefeng Yan.

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Appendixes A–C. The supporting information is available online at info.scichina.com and link. springer.com. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.

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Li, Z., Tian, L. & Yan, X. A novel deep quality-supervised regularized autoencoder model for quality-relevant fault detection. Sci. China Inf. Sci. 65, 159203 (2022). https://doi.org/10.1007/s11432-020-2964-7

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  • DOI: https://doi.org/10.1007/s11432-020-2964-7

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