摘要
针对工业对中小模数直齿圆柱齿距快速测量需求及视觉测量特点,提出一种基于齿廓图像边缘过渡带信息统计的单个齿距算法。该算法首先采用双阈值法提取齿轮齿廓边缘过渡带像素信息,然后根据齿轮渐开线几何关系,将过渡带像素信息逆向映射到基圆上,计算得到最优的齿廓边缘渐开线初始相位角,最后利用两条相邻同名齿廓初始相位角计算得出齿距。通过采用高精度量块组合边缘测量试验,验证了该算法的原理正确性和测量精度。结果表明,利用该算法视觉测量得到的相对位置最大偏差为0.0021mm,最大分散度为0.00052mm。对同一5级精度齿轮进行齿距测量,视觉齿轮测量仪和M＆M3525齿轮测量中心测量的最大单个齿距偏差出现在相同齿距上,二者相差0.0007mm,其齿距累积总偏差相差0.001mm,表明本齿轮齿距视觉测量方法可以满足5级精度直齿圆柱齿轮齿距的快速测量要求。
Aimed at the high efficient industial measurement demands of small and medium modulus spur gear pitch and the visional image feature,a new single pitch algorithm is proposed based on calculating the tooth image pixel information in gear edge transition zone. The algorithm first extracts the tooth image pixel information in gear edge transition zone with double threshold method. According to the involute geometric characteristics,this image pixel information is adversely mapped to the gear base circle. And the optimal initial phase angle of tooth profile edge involute is calculated. Finally,the gear pitch is obtained by using the initial phase angle of two adjacent corresponding tooth profile. The principle and measuring accuracy of the algorithm are verified by measuring experiments of combined edge obtained with high precision gauges. The results show that the maximum deviation of relative location using this algorithm vesical measurement is 0. 002 1 mm,and its maximum dispersity is 0. 000 52 mm. By measuring a same 5-level accuracy gear pitch,the gear maximum single pitch deviation obtained by visual measuring instrument occurs in the pitch same to that obtained by MM3525 gear measuring center. The difference between two results is 0. 000 7 mm and the difference of total cumulative deviation obtained by two methods is 0. 001 mm. These experimental results indicate that the pitch visual measuring method can meet the requirement of high efficient measurement for 5-level accuracy vertical cylinder gear pitch.
作者
支珊
赵文珍
赵文辉
段振云
孙禾
Zhi Shan;Zhao Wenzhen;Zhao Wenhui;Duan Zhenyun;Sun He(School of Mechanical Engineering,Shenyang University of Technology,Shenyang 110870,China;School of Electrical and Information Engineering, Liaoning Institute of Science and Technology, Benxi 117000, China)
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2018年第2期225-231,共7页
Chinese Journal of Scientific Instrument
基金
十二五国家科技支撑计划(2014BAF08B01)项目资助
关键词
视觉测量
齿距
局部图像特征
算法
visual measurement
pitch
local image feature
algorithm
