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一种基于人工蜂群算法优化化学镀Ni-P-Cu涂层工艺参数的实验方法

An Experimental Approach for Optimizing Coating Parameters of Electroless Ni-P-Cu Coating Using Artificial Bee Colony Algorithm.

作者信息

Roy Supriyo, Sahoo Prasanta

机构信息

Department of Mechanical Engineering, Jadavpur University, Kolkata 700032, India.

出版信息

Int Sch Res Notices. 2014 Oct 29;2014:976869. doi: 10.1155/2014/976869. eCollection 2014.

Abstract

This paper aims to present an experimental investigation for optimum tribological behavior (wear depth and coefficient of friction) of electroless Ni-P-Cu coatings based on four process parameters using artificial bee colony algorithm. Experiments are carried out by utilizing the combination of three coating process parameters, namely, nickel sulphate, sodium hypophosphite, and copper sulphate, and the fourth parameter is postdeposition heat treatment temperature. The design of experiment is based on the Taguchi L27 experimental design. After coating, measurement of wear and coefficient of friction of each heat-treated sample is done using a multitribotester apparatus with block-on-roller arrangement. Both friction and wear are found to increase with increase of source of nickel concentration and decrease with increase of source of copper concentration. Artificial bee colony algorithm is successfully employed to optimize the multiresponse objective function for both wear depth and coefficient of friction. It is found that, within the operating range, a lower value of nickel concentration, medium value of hypophosphite concentration, higher value of copper concentration, and higher value of heat treatment temperature are suitable for having minimum wear and coefficient of friction. The surface morphology, phase transformation behavior, and composition of coatings are also studied with the help of scanning electron microscopy, X-ray diffraction analysis, and energy dispersed X-ray analysis, respectively.

摘要

本文旨在基于四个工艺参数,利用人工蜂群算法对化学镀Ni-P-Cu涂层的最佳摩擦学行为(磨损深度和摩擦系数)进行实验研究。实验通过组合三个涂层工艺参数(即硫酸镍、次磷酸钠和硫酸铜)来进行,第四个参数是镀后热处理温度。实验设计基于田口L27实验设计。涂层制备完成后,使用带有块-滚配置的多摩擦测试仪对每个热处理样品的磨损和摩擦系数进行测量。结果发现,摩擦和磨损均随镍源浓度的增加而增加,随铜源浓度的增加而降低。人工蜂群算法成功用于优化磨损深度和摩擦系数的多响应目标函数。研究发现,在操作范围内,较低的镍浓度值、中等的次磷酸盐浓度值、较高的铜浓度值和较高的热处理温度值适合使磨损和摩擦系数最小。此外,还分别借助扫描电子显微镜、X射线衍射分析和能量色散X射线分析对涂层的表面形貌、相变行为和成分进行了研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0f5/4897047/3d392a360a4d/ISRN2014-976869.001.jpg

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