Abstract
In the current modern manufacturing industry, the demand for product quality control is increasing, as is the need for automation. However, the manual inspection may need to be noticed or undetectable in the complex production process. To solve this phenomenon, machine vision-based inspection of machine tools and their product features has become one of the key technologies in intelligent manufacturing. The basic principle of machine tool machine vision inspection is to transmit the object to be inspected to the computer through efficient image acquisition. Then, image processing or deep learning algorithms classify, locate, segment, and process the features of the thing. Finally, the computer makes the judgment of whether it is qualified. According to recent numerical analysis data, compared with traditional methods, machine tool machine vision inspection can improve the inspection efficiency by 30%, and the accuracy has reached 98%, much higher than manual inspection accuracy. This study provides an in-depth review of representative patents and machine tool vision inspectionpatents , and it comprehensively summarizes the research results from various dimensions in recent year. In the past five years, the average annual growth rate of machine tool vision inspection technology has reached 15%, showing the rapid development momentum of this field. The research content mainly focuses on designing vision detection structures, algorithm optimization designs, and personalized solutions for object differences.
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