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APPLICATION OF BACK-PROPAGATION NEURAL NETWORKS FOR CORROSION BEHAVIOR ESTIMATION OF Ni-TiN COATINGS FABRICATED THROUGH PULSE ELECTRODEPOSITION

Author

Listed:
  • DONGJIE GUO

    (State Laboratory of Surface & Interface, Zhengzhou University of Light Industry, Zhengzhou, China, 450002, China)

  • YUBING HAN

    (State Laboratory of Surface & Interface, Zhengzhou University of Light Industry, Zhengzhou, China, 450002, China)

  • CHUNYANG MA

    (#x2020;College of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, PR China)

  • WANYING YU

    (#x2020;College of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, PR China)

  • FAFENG XIA

    (#x2020;College of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, PR China)

  • MINZHENG JIANG

    (#x2020;College of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, PR China)

  • XIUYING XU

    (#x2020;College of Mechanical Science and Engineering, Northeast Petroleum University, Daqing 163318, PR China)

Abstract

In this paper, back-propagation (BP) neural network model with 8 hidden layers and 10 neurons was utilized to estimate corrosion behaviors of Ni-TiN coatings, deposited through pulse electrodeposition. Effects of plating parameters, namely, pulse frequency, TiN concentration and current density, on Ni-TiN coatings weight losses were discussed. Results indicated that pulse frequency, TiN concentration and current density had significant effects on weight losses of Ni-TiN coatings. Maximum mean square error of BP model was 9.10%, and this verified that the BP neural network model could accurately estimate corrosion behavior of Ni-TiN coatings. The coating fabricated at pulse frequency of 500Hz, TiN particle concentration of 8g/L and current density of 4A/dm2 consisted of fine grains and compact oxides, demonstrating that the coating displayed best corrosion resistance in this corrosion test. Concentrations of Ti and Ni in Ni-TiN coating prepared at pulse frequency of 500Hz, TiN particle concentration of 8g/L and current density of 4A/dm2 were 18.6at.% and 55.4at.%, respectively.

Suggested Citation

  • Dongjie Guo & Yubing Han & Chunyang Ma & Wanying Yu & Fafeng Xia & Minzheng Jiang & Xiuying Xu, 2019. "APPLICATION OF BACK-PROPAGATION NEURAL NETWORKS FOR CORROSION BEHAVIOR ESTIMATION OF Ni-TiN COATINGS FABRICATED THROUGH PULSE ELECTRODEPOSITION," Surface Review and Letters (SRL), World Scientific Publishing Co. Pte. Ltd., vol. 26(03), pages 1-8, April.
    • Handle: RePEc:wsi:srlxxx:v:26:y:2019:i:03:n:s0218625x18501548
    DOI: 10.1142/S0218625X18501548
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