• Chinese Journal of Quantum Electronics
  • Vol. 36, Issue 6, 699 (2019)
Weiyi WANG1、2、*, Qingshan XU1, and Minghan YANG3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: 10.3969/j.issn.1007-5461. 2019.06.009 Cite this Article
    WANG Weiyi, XU Qingshan, YANG Minghan. Method of system fault diagnosis based on optical gray-image recognition[J]. Chinese Journal of Quantum Electronics, 2019, 36(6): 699 Copy Citation Text show less
    References

    [3] Wang L, Liu Z, Miao Q, et al. Time-frequency analysis based on ensemble local mean decomposition and fast Kurtogram for rotating machinery fault diagnosis [J]. Mechanical Systems and Signal Processing, 2018, 103: 60-75.

    [6] Xie D, Li B. A hierarchical deep neural network for fault diagnosis on Tennessee-Eastman process [C]. IEEE International Conference on Machine Learning and Applications, 2016.

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    [11] Sun Kai, Gao Jianmin, Gao Zhiyong, et al. Plant-wide quantitative assessment of a process industry system’s operating state based on color-spectrum [J]. Mechanical Systems and Signal Processing, 2015, 60-61: 644-655.

    [13] Liu Z, Geng X, Xie Z, et al. The multi-core parallel algorithms of wavelet/wavelet packet transforms and their applications in power system harmonic analysis and data compression [J]. International Transactions on Electrical Energy Systems, 2015, 25(11): 2800-2818.

    [14] Budinich R. A region-based easy-path wavelet transform for sparse image representation [J]. International Journal of Wavelets Multiresolution and Information Processing, 2017, 15(5): 1750045.

    [16] Minghan Y, Jianye W, Shuai C, et al. Development of NPP digital I & C system closed-loop online test system based on signal transmission array [J]. Progress in Nuclear Energy, 2018, 108: 270-280.

    WANG Weiyi, XU Qingshan, YANG Minghan. Method of system fault diagnosis based on optical gray-image recognition[J]. Chinese Journal of Quantum Electronics, 2019, 36(6): 699
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