| Abstrakt: |
Measuring machining parameters is essential for influencing the quality and precision of the finished product in the manufacturing and machining industries. Machine vision systems, which provide an in-depth investigation of these parameters, are essential resources for this purpose. To evaluate machining parameters such as tool wear, surface roughness, and defects, this article investigates machine vision and its techniques. It also explores tool condition monitoring (TCM), a subject that is becoming more and more important. To achieve precision, high-resolution cameras with CCD or CMOS sensors in conjunction with deliberate illumination are essential. Area, compactness, and perimeter metrics are essential for assessing machining parameters because they offer insightful information about a variety of situations and enhance tool performance. By effectively utilizing these techniques, machinery can be converted into intelligent systems that improve safety, reliability, and product quality by preventing tool failure and optimizing cutting feed rates. A thorough review of the literature highlights the advantages of combining the direct and indirect TCM measurement methods, improving measurement accuracy. Additionally, the detection of tool wear problems like chipping, crater wear, and fractures is significantly aided by the integration of digital image processing techniques. [ABSTRACT FROM AUTHOR] |
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