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Defect intelligent identification in resistance spot welding ultrasonic detection based on wavelet packet and neural network
Authors:Jing Liu  Guocheng Xu  Lei Ren  Zhihui Qian  Luquan Ren
Affiliation:1.Department of Metallurgical and Materials Engineering,Nnamdi Azikiwe University,Awka,Nigeria
Abstract:Experimental correlation between varying processing and wear behaviour of ternary Ni-Co-SiO2 composites coating was investigated. The parameter used in this research are: SiO2 (5–25 wt%), thermal treatment (100–300 °C), applied load (5–15 N). The results show that novel ternary Ni-Co-SiO2 nanoparticle composite coating was successful applied to mild steel. The addition SiO2 nanoparticles in the coating Ni-Co bath lead to uniform microstructure. Thermal treatment of the coating at 300 °C decreased wear rate by (?0.031), increasing the wt% of SiO2 from 0 to 25 decreased the wear rate by ?0.018, applied load increases from 5 to 15 N raises the wear rate raises (0.0097), The lower wear rate was obtained at 25 wt% SiO2, applied load 5 N and thermal treatment at 300 °C. Validation of the results from pin on disc test with electro-hydraulic servo PV friction testing machine shows the same wear pattern. One can concluded in this work that the wear rate of the coated materials depend on the made up of the coating and not on the type of wear mechanism. It have be established in this work that thermal treatment and SiO2 nanoparticle can be used to enhance the wear behaviour of Ni-Co coating of mild steel.
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