Image Processing of Mg-Al-Sn Alloy Microstructures for Determining Phase Ratios and Grain Size and Correction with Manual Measurement

Abstract

The study of microstructures for the accurate control of material properties is of industrial relevance. Identification and characterization of microstructural properties by manual measurement are often slow, labour intensive, and have a lack of repeatability. In the present work, the intermetallic phase ratio and grain size in the microstructure of known Mg-Sn-Al alloys were measured by computer vision (CV) technology. New Mg (Magnesium) alloys with different alloying element contents were selected as the work materials. Mg alloys (Mg-Al-Sn) were produced using the hot-pressing powder metallurgy technique. The alloys were sintered at 620 °C under 50 MPa pressure in an argon gas atmosphere. Scanning electron microscopy (SEM) images were taken for all the fabricated alloys (three alloys: Mg-7Al-5Sn, Mg-8Al-5Sn, Mg-9Al-5Sn). From the SEM images, the grain size was counted manually and automatically with the application of CV technology. The obtained results were evaluated by correcting automated grain counting procedures with manual measurements. The accuracy of the automated counting technique for determining the grain count exceeded 92% compared to the manual counting procedure. In addition, ASTM (American Society for Testing and Materials) grain sizes were accurately calculated (approximately 99% accuracy) according to the determined grain counts in the SEM images. Hence, a successful approach was proposed by calculating the ASTM grain sizes of each alloy with respect to manual and automated counting methods. The intermetallic phases (Mg17Al12 and Mg2Sn) were also detected by theoretical calculations and automated measurements. The accuracy of automated measurements for Mg17Al12 and Mg2Sn intermetallic phases were over 95% and 97%, respectively. The proposed automatic image processing technique can be used as a tool to track and analyse the grain and intermetallic phases of the microstructure of other alloys such as AZ31 and AZ91 magnesium alloys, aluminium, titanium, and Co alloys.

Weld Strength of Friction Welding of Dissimilar Polymer Rods Fabricated by Fused Deposition Modeling

“…The difference in the mechanical properties Based on the results described above, the findings of this study provide the greatest application potential in the industry because this method is very practical and can be employed to join fluid mechanical components [45], transmission shafts [46], aircraft components, aerospace components, automotive components, or axle shafts using FRW. To further evaluate the tensile strength of FRW of dissimilar polymer rods fabricated by AM technology, test specimens can be prepared according to standards from ASTM International [47][48][49]. Thus, the research results can provide more application value in the industry.…”

Porosity Formation in Thin Welded Joints of Al–MG–LI Alloys

“…From the literature data [ 13 , 20 , 21 ], it is known that in the 1420 alloy directly after quenching in the water there is a certain amount of dispersed precipitation of the intermediate hardening phase (Al 3 Li). The decomposition of the supersaturated solid solution in 1420 alloy occurs according to the scheme: α→ (Al3Li)→ S1(AL2MgLi).…”

“…It is necessary to take into account that one of the important factors influencing the formation of quality welded joints is the humidity of shielding gas, which should be controlled. In addition, it is necessary to improve the protection of the weld root from oxidation and to perform chemical polishing of the welding wire [ 19 , 20 , 21 ].…”

A Multi-Flow Production Line for Sorting of Eggs Using Image Processing

“…Recently in many countries, small-scale factories have been transforming their production lines into automated solutions. Mostly, automated industrial grading processes include a Computer Vision System (CVS) because it provides swift calculations and accurate results in a short time [ 5 ] for detecting and discriminating agricultural products by their size and shape [ 6 ], dirt rate on production lines [ 7 , 8 , 9 ].…”