Automatic Measurement of Nanoimage Based on Machine Vision and Powder Metallurgy Materials

Abstract

The advantages of noncontact, high-efficiency, and fully automatic vision measurement technology make it widely used in industrial inspection and other fields. This study is based on the research of machine vision nanoimage automatic measurement and powder metallurgy materials. It aims to apply the machine vision imaging-related image processing technology principle to the automatic measurement of nanoimages and analyze the related properties of powder metallurgy materials and their image applications. This study mainly combines theory and practice to carry out experiments and data acquisition and analysis. On the one hand, it has a theoretical understanding of machine vision imaging principles and image segmentation; it also analyzes the properties and applications of powder metallurgy materials. On the other hand, on the basis of these theories, machine vision technology is fully applied to analyze the related physical properties such as the gap and density between tiny particles. Among them, the image measurement technology of moving targets is applied, and the model of the machine vision system is established. After a series of experimental verifications, the accuracy of the machine vision image measurements was fully guaranteed. The experimental results show that with the aid of machine vision technology, the accuracy of the observed data has been greatly increased; the maximum porosity of powder metallurgy materials has increased from 6.56 to 8.22; the maximum density has increased from 6.46 to 8.40. This demonstrates that automated image measurement based on machine vision technology can greatly improve the accuracy of measurements.