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To solve these problems, Viktor developed a bearing size detection system based on machine vision technology and image processing technology. Can achieve the objectivity of the test results, consistent detection results, safety and automated detection.
The system is used to automate the basic dimensional parameters of some standard mass-produced parts in the mechanical manufacturing industry, overcoming the drawbacks of random sampling manual inspections, liberating productivity, increasing productivity, and strengthening the market competitiveness of enterprises; its market application prospects Very broad. The system can be modified for on-line monitoring of workpiece identification, counting, and surface defect identification based on various customer requirements.
Bearing size detection system performance index
· Dimensional accuracy: within 0.01mm;
· Automatic sorting can be achieved for storing qualified products and unqualified products, respectively.
· Mechanical parameter setting: Due to different product sizes, mechanical parameters can be set according to the product, such as the size of the fixture, the transmission speed, the efficiency of the camera sampling, and so on.
• Alarm: After a defect is detected, the alarm light will flash within 0.1 seconds and an alarm sound will be issued.
· Statistics function: The system can automatically generate defect statistical reports, graphically represent defect statistics, and can print directly.
The bearing is a very important and widely used rotating part in the mechanical industry, and its production volume is large and its precision is high. However, at present, most bearing manufacturers in China still rely on mechanical and optical measuring instruments in the detection of bearing dimensions. They cannot achieve 100% inspection ratio and “zero waste rate†detection targets. Manual inspections are easy to produce visual fatigue. Therefore, the detection efficiency is low, the precision is low, and the application range is narrow.