Abstract
The uneven length of saw blade’s tooth width and pitch affects their life span seriously. At present, the manual measurements are mostly applied to inspect it, with low efficiency and low accuracy. This paper proposes a new method of measuring circular saw blades’ tooth width and pitch according to manual measurement based on vision measurement. The method uses techniques including threshold segmentation, feature extraction, morphology and sub-pixel. After preprocess, the smooth contours of saw blade can be got. On the basis of it, the number of teeth, tooth width and pitch length is obtained. By analyzing the experimental results, the average error of the method is 0.678 pixels, estimation error is 0.067 mm.
Highlights
Circular saw is a hard material cutting tools, which plays a significant role in cutting wood, stone, ceramics, steel and other materials
The shortcoming of low accuracy of manual welding, coupled with the constraints of production conditions, it will lead to the serious consequence of non-compliant tooth width and pitch
According to the characteristics of the manual measurements, there has a line between the cross point of measurement instrument and saw tooth, it needs to ensure the line perpendicular to a ray which is started from the center of the saw blade
Summary
Circular saw is a hard material cutting tools, which plays a significant role in cutting wood, stone, ceramics, steel and other materials. Other factors can reduce the life span, for example, the deficiency of missing teeth or big errors of tooth pitch and width. Take diamond saw blade as an example, which consists of the base body and the tooth (tool bit) with the connection method of manual welding. It’s need rigorous measurement inspection on tooth width and pitch of blade. The rate of qualified products can’t be guaranteed For this reason, a fast, high-precision detection method is in urgent need. Vision measurement(5) can provide fast, non-contact, high-precision solutions. This paper proposed a blade detection method based on visual measurement, shorten the measurement time and improve the measurement accuracy. The error is less than or equal to one pixel This method can be used in automatic vision measurement
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