工业视觉检测器在ZB45型卷烟封装机质量检测系统中的嵌入式应用

应用康耐视(COGNEX)的In-Sight5100-01工业视觉检测器,通过增加控制程序将卡纸缺失信号嵌入ZB45型卷烟封装机控制系统,处理了产品质量缺陷隐患,具有较强的推广性。

一种基于原机装置的烟包外观视觉检测器的设计

目前的烟包外观视觉检测器都是外挂式的,跟主机是分开运行的。本文设计了一种基于原机装置的烟包外观视觉检测器,应用于快速、准确地判断烟包外观质量是否符合产品质量要求的工业检测领域。该装置具有使用可靠,检测准确可靠,成本低廉等优点。At present, the visual detector of cigarette packs is external, which is running separately from the host. This paper designed a visual detector based on the original device for whether the appearance quality meets the product quality requirements. The device has the advantages of reliable use, accurate and reliable detection, and low cost.

视觉检测技术及应用

视觉检测技术，尤其是基于三角法的主动和被动视觉检测技术具有非接触、速度快、柔性好等特点，是一种先进的检测手段，适合现代制造业的需要。文章论述了视觉检测技术原理，讨论了已经研制的多个实际视觉检测系统，从不同角度展示了视觉检测技术在现代制造业中广阔的应用前景。

攀爬机器人末端位姿的视觉检测与控制

攀爬机器人末端夹持器位姿的自主调整是实现机器人自主攀爬的重要环节;在利用激光或声纳传感器进行位姿倾斜度检测时,会出现"夹持器摇摆现象",检测精确度不高而且耗时;针对这个问题,提出一种用于夹持器位姿倾斜检测的视觉检测器;检测器会在基于各向异性扩散滤波构建的多尺度空间提取图像的边缘信息,然后识别属于杆件的边缘直线,完成位姿倾斜度检测与控制;实验结果显示:检测器能较好地识别杆件边缘直线,精确计算出夹持器相对被夹杆件的倾斜度,时间约为0.8s;该检测器简洁实用,能较好地满足自主攀爬控制系统对精度和速度的需求。

Defect feature recognition method of glass fibre-reinforced structure based on visual image analysis

Glass fibre-reinforced(GFR)structure is extensively used in radome,spoiler and some other equipment.In engineering practice,due to the influence of wear,aging,impact,chemical corrosion of surface structure and other factors,the internal structure of this kind of structure gradually evolves into a defect state and expands to form defects such as bubbles,scratches,shorts,cracks,cavitation erosion,stains and other defects.These defects have posed a serious threat to the quality and performance of GFR structure.From the propagation process of GFR structure defects,its duration is random and may be very short.Therefore,designing a scientific micro defect intelligent detection system for GFR structure to enhance the maintainability of GFR structure will not only help to reduce emergencies,but also have positive theoretical significance and application value to ensure safe production and operation.Firstly,the defect detection mechanism of GFR structure is discussed,and the defect detection principle and defect area identification method are analyzed.Secondly,the processing process of defect edge signal is discussed,a classifier based on MLP is established,and the algorithm of the classifier is designed.Finally,the effectiveness of this method is proved by real-time monitoring and defect diagnosis of a typical GFR structure.The experimental results show that this method improves the efficiency of defect detection and has high defect feature recognition accuracy,which provides a new idea for the on-line detection of GFR structure defects.

Automated visual position detection and adjustment for optical waveguide chips and optical fiber arrays

The alignment coupling between optical waveguide chips and optical fiber arrays is the basis of the alignment coupling of planar optical waveguide devices, and the precise position detection with angle and spacing adjustments is one of the key steps of alignment coupling. A methodology for position detection, and angle and spacing adjustment was proposed for optical waveguide chips and optical fiber arrays based on machine vision. The experimental results show angle detection precision levels higher than 0.05°, line detection precision levels higher than 0.1 μm, and detection time less than 2 s. Therefore, the system developed herein meets the precise requirements necessary for position detection, and angle and spacing adjustments for optical waveguide chips and optical fiber arrays.

Hand-eye-vision based control for an inspection robot's autonomous line grasping

In order to ensure that the off-line arm of a two-arm-wheel combined inspection robot can reliably grasp the line in case of autonomous obstacle crossing,a control method is proposed for line grasping based on hand-eye visual servo.On the basis of the transmission line's geometrical characteristics and the camera's imaging principle,a line recognition and extraction method based on structure constraint is designed.The line's intercept and inclination are defined in an imaging space to represent the robot's change of pose and a law governing the pose decoupling servo control is developed.Under the integrated consideration of the influence of light intensity and background change,noise(from the camera itself and electromagnetic field)as well as the robot's kinetic inertia on the robot's imaging quality in the course of motion and the grasping control precision,a servo controller for grasping the line of the robot's off-line arm is designed with the method of fuzzy control.An experiment is conducted on a 1:1 simulation line using an inspection robot and the robot is put into on-line operation on a real overhead transmission line,where the robot can grasp the line within 18 s in the case of autonomous obstacle-crossing.The robot's autonomous line-grasping function is realized without manual intervention and the robot can grasp the line in a precise,reliable and efficient manner,thus the need of actual operation can be satisfied.

The Design of a Motion Control System for a Parallel Robot with Image Positioning

A motion control system for a parallel robot with image positioning was implemented in this paper. The system is composed of a machine vision device, a delta robot and a linear stage, and the concerned hardware, software and working methods were developed completely and verified successfully. During the phase of machine vision, the image of object was captured by camera, and then the process of smoothing filter, threshold algorithm and edge detection, was applied so as to obtain the edges of image. Finally, DV-GHT （Displacement Vector Generalized Hough Transformation） algorithm was used to recognize the center of multiple and arbitrary 2-D shapes objects. After the center of objects was recognized, the objects were delivered to the workspace of a delta robot by a motorized stage. Through the coordinate transformation between the camera and the robot system, the information of center can be converted to control commands for every working motors. Following, the delta robot picks up objects to the specified position sequentially by the trajectory planning and tracking controls. The software of C＋＋/CLI is used to achieve the phase of motion controls and the program of DV-GHT is used to detect and conduct the positions for four different characteristics of the objects simultaneously so as to indicate the delta robot to classify the objects successfully.

Face Detection Technology Based on Robot Vision

One being developed automatic sweep robot, need to estimate if anyone is on a certain range of road ahead then automatically adjust running speed, in order to ensure work efficiency and operation safety. This paper proposed a method using face detection to predict the data of image sensor. The experimental results show that, the proposed algorithm is practical and reliable, and good outcome have been achieved in the application of instruction robot.

Specific-Scene Oriented Pedestrian Detection in Visual Sensor Network

Pedestrian detection is one of the most important problems in the visual sensor network. Considering that the visual sensors have limited cap ability, we propose a pedestrian detection method with low energy consumption. Our method contains two parts: one is an Enhanced Self-Organizing Background Subtraction (ESOBS) based foreground segmentation module to obtain active areas in the observed region from the visual sensors; the other is an appearance model based detection module to detect the pedestrians from the foreground areas. Moreover, we create our own large pedestrian dataset according to the specific scene in the visual sensor network. Numerous experiments are conducted in both indoor and outdoor specific scenes. The experimental results show that our method is effective.