Hardness determination by a semi-automatic testing system

Abstract

The hardness testing is vital for metals for testing and production quality control. Hardness testing is a fine indicator to determine the mechanical characteristics of metals. The various types of hardness testing methods include Rockwell, Vicker, Brinell, and Knoop testing methods. The most prevalent manual method to determine hardness is indentation using dead weight technology. However, the said technology is quite ancient and it has its own limitations, like the kinetic effect applying excessive load at actual, man-to-man variations, variation over the period due to deterioration and friction effects of moving parts like lever, weight block hanger, etc. increases the uncertainty of this method and eventually demands for upgradation of the technology. Further, the methods currently in use are open-loop and manually operated testers. The main drawback of all these testers is that they provide zero feedback, and so the obtained result needs to be compared to the desired result. To overcome the above-stated problem, the paper presents some novel modifications for measuring hardness using existing methods of Rockwell, Vicker, and Brinell testing. Toward this objective, the paper proposes to modify existing testers and develop a semiautomatic hardness testing system. Firstly, for Rockwell testing, the work aims to design a closed-loop system for hardness testing. The proposed system comprises of Arduino as an open microcontroller, a load cell along with servo motor, and its driver to establish the desired closed loop. The need of obtaining a more accurate result, free from human interference gives rise to a closed-loop system for hardness testing. The key aspect of the closed-loop system lies in retaining the basic structure of the metal. Unlike traditional hardness tester, during testing, the weight increases gradually, due to which the basic structure of metal is not deformed. Secondly, the paper proposes a computational methodology that would estimate the Vickers and Brinell hardness value. The proposed system comprises of a camera for gathering hardness indentation images, thereby automating the system. Further, these images are analyzed based on image processing software, and the indentation depth is obtained. The proposed work thus replaces human intervention to calculate the hardness of the material. The results obtained based on the proposed systems provide a proof of concept to address the problems of traditional Rockwell, Vicker, and Brinell testing.