A Novel Image Processing Technique for Analyzing Wear Worn Surface Roughness and Corrosion Behavior of Sintered Mg/B4C Composites

Autor: C. Emmy Prema, S. Suresh, M. Navaneetha Krishnan, S.C. Vettivel, C. P. Jesuthanam
Rok vydání: 2020
Předmět:
Zdroj: Transactions of the Indian Institute of Metals. 74:51-68
ISSN: 0975-1645
0972-2815
DOI: 10.1007/s12666-020-02123-3
Popis: The pure Mg and Mg-B4C composites are produced with dissimilar weight percentages (Mg-5% B4C, Mg-10% B4C, and Mg-15% B4C) using powder metallurgy methods. To find the consequences of B4C in pure Mg, the Vickers micro-hardness, dry sliding wear, 3D roughness profile, and immersion corrosion tests were conducted. To quantify the texture of the composite surface, the local binary co-occurrence pattern quantification technique was used in this analysis and the related texture features were extracted to evaluate the composite surfaces. The wear analysis of Mg-B4C composites was examined in disparate loads of 30, 60, and 90 N with a constant sliding velocity of 2 m/s and in 2000 m constant sliding distance. The changes in wear rate, wear depth, and friction coefficient were compiled and analyzed. It was identified that the wear rate increased with the increment of load. To comprehend the wear mechanism of pure Mg and all Mg-B4C (5–15%) composites, its worn surfaces were subjected to SEM and EDS mapping analyses. The surface roughness of the worn surfaces was explored using a 3D roughness profile test and atomic force microscopy analysis. The obtained results exhibited that the hardness of Mg-B4C composites increased with increasing of B4C weight percentages. The rate of corrosion was discovered using the weight loss method. The corrosion rate decreased to a great extent with the increasing weight percentage of B4C in the Mg matrix.
Databáze: OpenAIRE
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