CAJ | 학술논문

　　传统的凸轮轴表面缺陷多为产后抽检，相比在线全检存在漏检与缺陷率上升等现象，且只能事后发现；而人工在线全检不但会使成本上升、也对人力资源提出了考验。为此实现自动实时在线全检就成为急需解决的课题。设计了基于机器视觉的凸轮轴表面缺陷在线自动检测系统。系统安装在凸轮轴生产流水线两侧，搭建特定光源，在凸轮轴移动、停止、旋转过程中通过高速相机对其表面进行图像捕获，并由工控机进行缺陷判定与定位。根据轴类表面缺陷的特征，设计了缺陷分割算法和缺陷区域标记算法，对凸轮轴表面的外伤、砂眼、研磨不良等典型缺陷进行分辨。算法可以准确提取目标缺陷区域，标记缺陷位置并统计缺陷特征对缺陷进行判定。该系统可在0.44 s每根轴的速度下，检测出凸轮轴表面直径大于1 mm的缺陷，并通过人机交互界面显示缺陷所在位置。完全可以取代产后抽检及人工在线全检，同时还可以提高检测效率与检测精度。
　　전통적철륜축표면결함다위산후추검，상비재선전검존재루검여결함솔상승등현상，차지능사후발현；이인공재선전검불단회사성본상승、야대인력자원제출료고험。위차실현자동실시재선전검취성위급수해결적과제。설계료기우궤기시각적철륜축표면결함재선자동검측계통。계통안장재철륜축생산류수선량측，탑건특정광원，재철륜축이동、정지、선전과정중통과고속상궤대기표면진행도상포획，병유공공궤진행결함판정여정위。근거축류표면결함적특정，설계료결함분할산법화결함구역표기산법，대철륜축표면적외상、사안、연마불량등전형결함진행분변。산법가이준학제취목표결함구역，표기결함위치병통계결함특정대결함진행판정。해계통가재0.44 s매근축적속도하，검측출철륜축표면직경대우1 mm적결함，병통과인궤교호계면현시결함소재위치。완전가이취대산후추검급인공재선전검，동시환가이제고검측효솔여검측정도。
Compared with the on-line detection in production, traditional detection systems of camshafts'surface defect are mostly sampling after production in which missing rates and deficiencies rates are increased that can not be discovered until detection is completed, while full manually online detection not only increases the cost but also challenges the human resources. Therefore it is an important research subject to realize automatic real-time online detection. In this paper, a detection system of surface defect based on computer vision was designed. In this system, certain illuminants were constructed on both sides of the production line which surface images were captured by a high-speed camera and decided and located by an industrial computer while camshafts moved, stopped and rotated. For processing typical defect such as pit, pinhole porosity and rough surface, a defect segmentation algorithm and defect area marker algorithm were designed on the basis of defect features of camshaft surface. Target defect area was extracted accurately by the algorithms, defect locations were marked as well as the defect features were computed for final judgments. In this system, defect in camshaft surface which diameter is greater than 1 mm can be detected at 0.44 s/axis and locations of detect were displayed through human-machine interactive interface. Traditional sampling detection after production and full manually online detection can be completely replaced, meanwhile, the accuracy and efficiency are improved.