• Electronics Optics & Control
  • Vol. 27, Issue 10, 83 (2020)
WANG Yun1, JING Bo2, HUANG Yifeng2, and JIAO Xiaoxuan2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2020.10.017 Cite this Article
    WANG Yun, JING Bo, HUANG Yifeng, JIAO Xiaoxuan. Fault Diagnosis of DWT-SVM for Airborne Equipment Based on DSP+FPGA Architecture Platform[J]. Electronics Optics & Control, 2020, 27(10): 83 Copy Citation Text show less
    References

    [4] JIAO X X, JING B, HUANG Y F, et al.Research on fault diagnosis of airborne fuel pump based on EMD and probabilistic neural networks[J].Microelectronics Reliability, 2017, 75:296-308.

    [7] YU J S, MO B H, TANG D Y, et al.Remaining useful life prediction for lithium-ion batteries using a quantum particle swarm optimization-based particle filter[J].Quality Engineering, 2017, 29(3):536-546.

    [9] DURODOLA J F, LI N, RAMACHANDRA S, et al.A pattern recognition artificial neural network method for random fatigue loading life prediction[J].International Journal of Fatigue, 2017, 99(6):55-67.

    [10] SEPASI S, GHPRBANI R, LIAW B Y.A novel on-board state-of-charge estimation method for aged Li-ion batteries based on model adaptive extended Kalman filter[J].Journal of Power Sources, 2014, 245(1):337-344.

    [12] KHELIF R, CHEBEL-MORELLO B, MALINOWSKI S, et al.Direct remaining useful life estimation based on support vector regression[J].IEEE Transactions on Industrial Electronics, 2017, 64(3):2276-2285.

    [13] LIN C J.A comparison of methods for multiclass support vector machines[J].IEEE Transactions on Neural Networks, 2002, 13(2):415-425.

    WANG Yun, JING Bo, HUANG Yifeng, JIAO Xiaoxuan. Fault Diagnosis of DWT-SVM for Airborne Equipment Based on DSP+FPGA Architecture Platform[J]. Electronics Optics & Control, 2020, 27(10): 83
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