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

Dongjie Guo, Yubing Han, Chunyang Ma, Wanying Yu, Fafeng Xia, Minzheng Jiang and Xiuying Xu
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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

Surface Review and Letters (SRL), 2019, vol. 26, issue 03, 1-8

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.

Keywords: BP neural network; estimate; Ni-TiN coating; corrosion behavior (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1142/S0218625X18501548

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