Diameter detection mechanism for shaft-class parts

Abstract

The invention relates to a diameter detection mechanism for shaft-class parts. A substrate is provided with a plurality of vertical uprights of which the lower ends are connected with the substrate; the upper ends of the vertical uprights are provided with a horizontal supporting plate; the supporting plate is provided with vertical lifting air cylinders; the piston ends of the lifting air cylinders are connected with a horizontal clamping air cylinder; two piston ends of the clamping air cylinder are connected with pushing tip frames; each pushing tip frames are provided with a pushing tip; the lower end surface of the substrate is provided with two opposite detection air cylinders; the detection air cylinders are vertical to the pushing tips; the piston ends of the detection air cylinders face a position between the two pushing tips; the piston end of each detection air cylinder is connected with a sensor frame; each sensor frame is provided with a contact type sensor; and the lowerend surface of the substrate is provided with a plurality of supports adjacent to the edges of the substrate. Compared with the prior art, the diameter detection mechanism of the invention has the advantages of high detection precision, accurate data and the like.

Description

technical field [0001] The invention relates to a detection mechanism, in particular to a detection mechanism for shaft parts. Background technique [0002] Shaft parts are very common parts in the machinery industry, and they are also very important parts. The shape error accuracy directly affects the motion performance and service life of the machine. With the development of the machinery industry, the requirements for shafts are getting higher and higher. When detecting the diameter of parts, the traditional detection is to use pure artificial vision detection or the combination of artificial vision with mechanical measuring tools and optical instruments. Manual detection often has disadvantages such as low efficiency, poor reliability, low detection accuracy, and high cost; using Industrial camera detection, the detection accuracy is not high, the detection data is not stable enough, and it is greatly affected by external light; neither manual nor industrial camera detec...

AI Technical Summary

Problems solved by technology

[0002] Shaft parts are very common parts in the machinery industry, and they are also very important parts. The shape error accuracy directly affects the motion performance and service life of the machine. With the development of the machinery industry, the requirements for shafts are getting higher and higher. When detecting the diameter of parts, the traditional detection is to use pure artificial vision detection or the combination of artificial vision with mechanical measuring tools and optical instruments. Manual detection often has disadvantages such as low efficiency, poor reliability, low detection accuracy, and high cost; using Industrial camera detection, the detection accuracy is not high, the detection data is not stable enough, and it is greatly affected by external light; neither manual nor industrial camera detection can realize automatic detection on the production line, and the parts need to be installed manually, which seriously affects the processing efficiency

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