Application of BP Artificial Neural Network in Preparation of Ni-W Graded Coatings.

Pei Feng,Yuhua Shi,Peng Shang,Wenyuan Zhang,Rongrong Feng,Hanjun Wei,Tongtong Peng,Lisha Pang

doi:10.3390/ma14226781

Abstract

The internal stress difference between soft-ductile aluminum alloy substrate and hard-brittle Ni–W alloy coating will cause stress concentration, thus leading to the problem of poor bonding force. Herein, this work prepared the Ni–W graded coating on aluminum alloy matrix by the pulse electrodeposition method in order to solve the mechanical mismatch problem between substrate and coatings. More importantly, a backward propagation (BP) neural network was applied to efficiently optimize the pulse electrodeposition process of Ni–W graded coating. The SEM, EDS, XRD, Vickers hardness tester and Weighing scales are used to analyze the micromorphology, chemical element, phase composition, and micro hardness as well as oxidation weight increase, respectively. The results show that the optimal process conditions with BP neural network are as follows: the bath temperature is 30 °C, current density is 15 mA/cm2 and duty cycle is 0.3. The predicted value of the model agrees well with the experimental value curve, the relative error is minor. The maximum error is less than 3%, and the correlation coefficient is 0.9996. The Ni–W graded coating prepared by BP neural network shows good bonding with the substrate which has flat and smooth interface. The thickness of the coating is about 136 μm, which slows down the oxidation of the substrate and plays an effective role in protecting the substrate.

Highlights

Aluminum alloy has been widely used in the mechanical manufacturing and aerospace fields due to its advantages of low density, superior electrical and thermal conductivity and optimal ductility [1,2,3]
Pulse electrodeposition of Ni–W coatings shows the superiority of fine crystallization, smooth and bright and fast film formation rate, which could enhance the hardness, high temperature oxidation resistance of aluminum alloy substrates [10,11,12,13]
The Ni–W alloy coating and further Ni–W graded coating were prepared by the optimal pulse electrodeposition parameters (T1 C3 D3 ), with the bath temperature of 30 ◦ C, current density of 15 mA/cm2 and duty cycle of 0.3 simulated by backward propagation (BP) neural network

Summary

Introduction

Aluminum alloy has been widely used in the mechanical manufacturing and aerospace fields due to its advantages of low density, superior electrical and thermal conductivity and optimal ductility [1,2,3] Certain disadvantages, such as low hardness and the fact that it is oxidized at high temperature, limit its service life and wide application [4]. Protective coating can be prepared on the surface of aluminum alloy to solve this problem In this case, Ni–W coating has attracted extensive attention due to its excellent hardness, corrosion resistance and high temperature oxidation resistance as well as other properties [5,6,7,8,9].

Methods

Results

Conclusion