The Precise Test System Of Double Gear Size Based On Machine Vision Technology

Due to driving stably and precise size.fine-pitch gears are widely used in watches, aviation instrument and precise optical instruments.The fine-pitch gear has complex structure.small size and many parameters need to measure,which brought a certain degree of difficulty to the gear measurement.Most of the domestic gear manufacturers adopt the traditional contact measurement methods.this method not only workload big, long measuring time, low accuracy, and is not suitable for online testing during production.Research on gear measurement method based on machine vision and virtual instrument technology, not only can achieve on-line precise measurement, but also has the advantages of stable and reliable, high automation and high intelligence.Using the camera to capture the the gear image information, calculating the gear parameters,and judging by computer, this paper developed a system of gear quality automatic image measurement.The system involutes spur gear real-time image processing and geometric parameters of the non-contact online measurement.According to the double gear’s structure and the demand of the quality measurement.the paper selects adapted industry digital vidicon, camera lens and lamp-source after considering the precision and cost. The paper profoundly studies the problem of gear image digital filtering and image segmentation, presents the incision synthetic method of threshold iteration with maximum classes variance, which solves the problem of image segmentation of big and small gears.The edge extraction is accurate to1/10sub-pixel level with IMAQ Vision Senior edge detection.The paper make full use of LabVIEW and IMAQ Vision software,detect the size of the gear hole size, pitch, modulus, single pitch deviation, cumulative pitch deviation, and so on.Experiments show that, the system can automatically and reliably measuring gear size, through the intelligent judgment, shave the unqualified products, measurement accuracy of testing requirements. Not only does it reduce the manual workload and improve the measurement efficiency, but also make entire production system more intelligent and more automated.The system will have a broad market prospect.