Earticle

Laser vision inspection systems are becoming popular for automated inspection of manufactured components. The performance of such systems can be enhanced by improving accuracy of the hardware and robustness of the software used in the system. This paper presents a new approach for enhancing the capability of a laser vision system by applying hardware compensation and using efficient analysis software. A 3D geometrical model is developed to study and compensate for possible distortions in installation of gantry robot on which the vision system is mounted. Appropriate compensation is applied to the inspection data obtained from the laser vision system based on the parameters in 3D model. The present laser vision system is used for dimensional inspection of car chassis sub frame and lower arm assembly module. An algorithm based on simplex search techniques is used for analyzing the compensated inspection data. The details of 3D model, parameters used for compensation and the measurement data obtained from the system are presented in this paper. The details of search algorithm used for analyzing the measurement data and the results obtained are also presented in the paper. It is observed from the results that, by applying compensation and using appropriate algorithms for analyzing, the error in evaluation of the inspection data can be significantly minimized, thus reducing the risk of rejecting good parts.

A control rod device (CRD) nozzle attaches to the hemispherical surface of a reactor head with J-groove welding. Primary water stress corrosion cracking (PWSCC) causes degradation in these welds, which requires that these defect areas be repaired. To perform this repair welding automatically on a complicated weld groove shape, an auto-welding system was developed incorporating a laser vision sensor that measures the 3-dimensional (3D) shape of the groove and a weld-path creation program that calculates the weld-path parameters. Welding trials with a J-groove workpiece were performed to establish a basis for developing this auto-welding system. Because the reactor head is placed on a lay down support, the outer-most region of the CRD nozzle has restricted access. Due to this tight space, several parameters of the design, such as size, weight and movement of the auto-welding system, had to be carefully considered. The cross section of the J-groove weld is basically an oval shape where the included angle of the J-groove ranges from 0 to 57 degrees. To measure the complex shape, we used double lasers coupled to a single charge coupled device (CCD) camera. We then developed a program to generate the weld-path parameters using the measured 3D shape as a basis. The program has the ability to determine the first and final welding positions and to calculate all weld-path parameters. An optimized image-processing algorithm was applied to resolve noise interference and diffused reflection of the joint surfaces. The auto-welding system is composed of a 4-axis manipulator, gas tungsten arc welding (GTAW) power supply, an optimized designed and manufactured GTAW torch and a 3D laser vision sensor. Through welding trials with 0 and 38-degree included-angle workpieces with both J-groove and U-groove weld, the performance of this auto-welding system was qualified for field application.

본 논문은 머신비전시스템에서 정확한 이미지 획득을 위한 방법을 제안한다. 각종 렌즈에서 요구되는 가장 중요한 기능으로는 실물과 동일한 고품질의 결상을 구현하는 광학적 역할이다. 그러나 머신비전시스템의 입력부에서는 렌즈의 수차로 인하여 왜곡현상이 발생한다. 이러한 문제를 해결하기 위해 실세계 좌표계와 영상 좌표계 간의 변환 관계를 정의해주는 매핑 기능으로, 행렬연산을 통하여 두 좌표간의 거리를 계산하여 정확한 위치를 지정하게 된다. 레이저 정밀 가공작업에서도 Galvanometer를 사용하면 비구면 초점 렌즈에 의하여 발생되고 있는 렌즈 수차를 보정하여야 가공 오차를 개선 할 수 있다. 비구면 렌즈의 수차는 2차원 곡선의 형태를 가지고 있으나, 기존의 렌즈 보정 방법인 선형방법은 매우 많은 점들을 검사하여 보정시간이 많이 소요되는 문제점이 있었다. 가공장비에서 렌즈의 수차로 인하여 발생하는 가공오차를 감소시키기 위하여 Bilinear interpolation 기법을 적용하는 방법을 제안하였다. 제안한 방법은 기존 선형방법과 비교하여 위치 오차의 평균값과 표준편차가 향상되었음 실험을 통하여 입증하였으며 실제 레이저 응용업무에 적용하고 있다.

We propose a method for accurate image acquisition in a machine vision system in the present study. The most important feature is required by the various lenses to implement real and of the same high quality image-forming optical role. The input of the machine vision system, however, is generated due to the aberration of the lens distortion. Transformation defines the relationship between the real-world coordinate system and the image coordinate system to solve these problems, a mapping function that matrix operations by calculating the distance between two coordinates to specify the exact location. Tolerance Focus Lens caused by the lens aberration correction processing to Galvanometer laser precision machining operations can be improved. Aberration of the aspheric lens has a two-dimensional shape of the curve, but the existing lens correction to linear time-consuming calibration methods by examining a large number of points the problem. How to apply the Bilinear interpolation is proposed in order to reduce the machining error that occurs due to the aberration of the lens processing equipment.

The paper studies about a line-laser based vision system to measure structural adhesive as a non-invasive inspection. It proposes a novel vision system to measure height and width of adhesive (or object) by optical triangulation using line-laser, and analyzes for resolution, gaze angle, focal length and baseline of vision camera, proper to measurement. The validity of the proposed method was verified through actual measurement of structural adhesive.

In the multi-pass welding of pressure vessels or ships, the mechanical touch sensor system is generally used together with a manipulator to measure the gap and depth of the narrow gap to perform seam tracking. Unfortunately, such mechanical touch sensors may commit measuring errors caused by the deterioration of the measuring device. An automation system of narrow gap multi-pass welding using a laser vision system which can track the seam line of narrow gap and which can control welding power has been developed. The joint profile of the narrow gap, with 250mm depth and 28mm width, can be captured by laser vision camera. The image is then processed for defining tracking positions of the torch during welding. Then, the real-time correction of lateral and vertical position of the torch can be done by the laser vision system. The adaptive control of welding conditions like welding currents and welding speeds, can also be performed by the laser vision system, which cannot be done by conventional mechanical touch systems. The developed automation system will be adopted to reduce the idle time of welders, which happens frequently in conventional long welding processes, and to improve the reliability of the weld quality as well.

In this page, we developed the inspection system for automobile parts using the laser vision sensor. Laser vision sensor has gotten 2 dimensions information and third dimension information of laser vision camera using the vision camera. Used JIG and ROBOT for inspection position transfer. Also, computer integration system developed that control system component pal1s and manage data measurement information. Compare sensor measurement result with CAD Data and verified measurement result effectiveness taking advantage of CAD to get information of measurement object.

Various scanning systems have been studied in many industrial areas to acquire a range data or to reconstruct an explicit 3D model. Currently optical technology has been used widely by virtue of noncontactness and high-accuracy. In this paper, we describe a 3D laser scanning system developped to reconstruct the 3D surface of a large-scale object such as a curved-plate of ship-hull. Our scanning system comprises of 4ch-parallel laser vision modules using a triangulation technique. For multi laser vision, calibration method based on least square technique is applied. In global scanning, an effective method without solving difficulty of matching problem among the scanning results of each camera is presented. Also minimal image processing algorithm and robot-based calibration technique are applied. A prototype had been implemented for testing.

본 연구에서는 구조물의 변위 측정을 위한 비접촉식 센서 시스템의 개선 방안을 제시하였다. 기존의 접촉식 센서인 LVDT는 높은 정확도를 제공하지만 설치가 어렵고 장기 사용 시 마모 및 변형 우려가 있으며, 비접촉식 LDS는 물리적 접촉 없이 측정할 수 있으나 정확도가 제한적이다. 이에 본 연구에서는 레이저 빔과 웹카메라를 활용한 비접촉식 변위 측정 방법을 제안하고, 다점 측정이 가능한 경제적인 교량 처짐 측정 시스템을 구축하였다. 또한, 인공지능 기반의 고정밀 측정 기술을 개발하여 변위 측정 정확도와 효율성을 향상시켰으며, 학습된 모델로 예측한 X-좌표의 최대, 최소차는 0.0484과 0.0854 mm, Y-좌표의 최대, 최소차는 0.0625과 0.0596 mm로 예측이 가능하였다.

This study proposes an improved non-contact sensor system for measuring structural displacement. While traditional contact-type sensors such as LVDTs offer high accuracy, they are difficult to install and may suffer from wear or deformation over long-term use. On the other hand, non-contact sensors like LDS can perform measurements without physical contact but often lack sufficient accuracy. To address these limitations, this research introduces a non-contact displacement measurement method utilizing a laser beam and a webcam. An economical multi-point bridge deflection measurement system was developed based on this approach. Furthermore, an AI-based high-precision measurement technique was implemented to enhance both the accuracy and efficiency of displacement estimation. The trained model achieved a maximum and minimum prediction error of 0.0484 mm and 0.0854 mm for the X-coordinate, and 0.0625 mm and 0.0596 mm for the Y-coordinate, respectively.

The primary aim of this paper is to develop an automated welding system capable of adapting to variation in the weld seam center in order to allow higher welding speeds and improved welding quality by using a laser vision sensor. The system is designed to compensate for production problems such as pipe ovality, variation in bevel geometry and track misalignment.

본 논문은 레이저 비젼 센서를 이용하여 측정 대상의 3차인 위치 정보를 측정하기 위한 방법을 제안하였으며, 이를 이용한 측정 시스템을 개발하였다. 레이저센서는 물체의 평면방정식을 찾기 위해 사용되었으며, 측정된 물체의 평면의 방정식과 Camera를 이용한 물체 위치 정보와 함께 측정 대상의 3차원 정보를 얻는다. 이러한 고정밀 고속 계측을 위한 레이저 모듈 및 소프트웨어를 개발하고 전용 JIG장치에 의하여 측정하던 방식을 Robot과 Laser Vision Sensor를 이용하여 자동으로 측정하는 시스템을 구현하였다.

In this paper, we propose a laser vision sensor based welding quality inspection algorithm, and implement a welding quality inspection system for fillet welds. Welding quality control is very important in the automotive industry. The proposed inspection algorithm examines mandatory inspection items requested by the person in charge of various types of welding defect. Laser vision sensor based welding quality inspection system composed of laser vision sensor, electronic rotary and inspection PC that inspection program installed. Laser vision sensor is a device that acquires laser profile data from the cross section of the weld and consists of a 3D camera and line laser module. The electric rotary serves to transport the laser vision sensor to inspect the weld bead along the nut's perimeter. The inspection program controls the laser vision sensor and the electric rotary. It also provides GUI for monitoring test results. A specimen was prepared for the performance evaluation of the welding quality inspection system. The experimental results show that the system and the inspection algorithm implemented by the proposed algorithm effectively detect important defects in various production sites.

A vision sensor measure range data using laser light source, This sensor generally use patterned laser which shaped single line. But this vision sensor cannot satisfy new trend which needs faster and more precise processing. The sensor's sampling rate increases as reduced image processing time. However, the sampling rate can not over 30fps, because a camera has mechanical sampling limit. If we use multi line laser pattern, we will measure multi range data in one image. In the case of using same sampling rate camera, number of 2D range data profile in one second is directly proportional to laser line's number. For example, the vision sensor using 5 laser lines can sample 150 profiles per second in best condition.

Because of its fast and precise welding performance, laser welding is becoming a new excellent welding method. However, the precise focusing and robust seam tracking are required to apply laser welding to the practical fields. In order to laser weld a type of T joint like a circular pipe on a square pipe, which could be met in the three dimensional structure such as an aluminum space frame, a visual sensor system was developed for automation of focusing and seam tracking. The developed sensor system consists of a digital CCD camera, a structured laser, and a vision processor. It is moved and positioned by a 2-axis motorized stage, which is attached to a 6 axis robot manipulator with a laser welding head. After stripe-type structured laser illuminates a target surface, images are captured through the digital CCD camera. From the image, seam error and defocusing error are calculated using image processing algorithms which includes efficient techniques handling continuously changed image patterns. These errors are corrected by the stage off-line during welding or teaching. Laser welding of a circular pipe on a square pipe was successful with the vision tracking system by reducing the path positioning and de focusing errors due to the robot teaching or a geometrical variation of specimens and jig holding.