Laser Stripe Research Articles

Automatic recognition system of welding seam type based on SVM method

In this paper, an automatic recognition system of welding seam type based on support vector machine (SVM) method is presented. The hardware of the proposed system consists of an industry robot with six degrees of freedom, a vision sensor, and a computer. The system has two parts including input feature vector computation and model building. In the input feature vector computation part, the depth values of a series of points of the welding joint are taken as feature vector, which are determined by four steps including main line extraction of the laser stripe, normalization of the laser stripe, selection of the left and right edge points of the welding joint, and normalization of feature vectors. In the model building part, SVM-based modeling method is used to achieve welding seam type recognition. At first, RBF kernel function is employed for classification of welding seam types. Then, the parameters of RBF are determined by a grid search method using cross-validation. After the optimal parameters of RBF being determined, the SVM model is built, and it could be used to predict welding seam type. Finally, a series of welding seam type recognition experiments are implemented. Experimental results show that the proposed system can achieve welding seam type recognition accurately and the computation cost can be reduced compared with previous methods.

Robust laser stripe extraction for three-dimensional reconstruction based on a cross-structured light sensor.

Cross-structured light sensor architecture for 3D reconstruction was established. An improved center of mass method was proposed for laser stripe extraction. For each initial laser stripe center point, the center of mass method was performed along the normal direction that was calculated using the Hessian matrix. The normal directions can be used to divide the laser stripe center points into two categories. Laser stripe extraction experiments showed that the proposed method is fast and robust. 3D reconstruction of a cylinder was used to analyze reconstruction accuracy, with relative accuracy of less than 0.15 mm. 3D reconstruction of a shoe last showed that cross-structured light sensors can obtain more abundant information than single-structured light sensors.

Modeling and Calibration of a Novel One-Mirror Galvanometric Laser Scanner.

A laser stripe sensor has limited application when a point cloud of geometric samples on the surface of the object needs to be collected, so a galvanometric laser scanner is designed by using a one-mirror galvanometer element as its mechanical device to drive the laser stripe to sweep along the object. A novel mathematical model is derived for the proposed galvanometer laser scanner without any position assumptions and then a model-driven calibration procedure is proposed. Compared with available model-driven approaches, the influence of machining and assembly errors is considered in the proposed model. Meanwhile, a plane-constraint-based approach is proposed to extract a large number of calibration points effectively and accurately to calibrate the galvanometric laser scanner. Repeatability and accuracy of the galvanometric laser scanner are evaluated on the automobile production line to verify the efficiency and accuracy of the proposed calibration method. Experimental results show that the proposed calibration approach yields similar measurement performance compared with a look-up table calibration method.

Field Geometric Calibration Method for Line Structured Light Sensor Using Single Circular Target

To achieve fast calibration of line structured light sensor, a geometric calibration approach based on single circular calibration target is proposed. The proposed method uses the circular points to establish linear equations, and according to the angle constraint, the camera intrinsic parameters can be calculated through optimization. Then, the light plane calibration is accomplished in two steps. Firstly, when the vanishing lines of target plane at various postures are obtained, the intersections between vanishing lines and laser stripe can be computed, and the normal vector of light plane can be calibrated via line fitting method using intersection points. After that, the distance from the origin of camera coordinate system to the light plane can be derived based on the model of perspective-three-point. The actual experimental result shows that this calibration method has high accuracy, its average measuring accuracy is 0.0451 mm, and relative error is 0.2314%. In addition, the entire calibration process has no complex operations. It is simple, convenient, and suitable for calibration on sites.

New Concepts for Quality Assurance of Lightweight Material

Lightweight material became more and more important during the last years. To ensure a defect-free production, effective measurement solutions for quality assurance are necessary. The Laser stripe sensors enable the evaluation of form deviations. For the detection of internal defects thermography provides a suitable solution. On this account the combination of these two non-destructive testing principles gives an opportunity to detect different kinds of defects regarding the outer geometry and the material within the parts. This paper deals with varied concepts to combine laser stripe sensor system and thermography and shows the potential of these methods.

Global Measurement Method for Large-Scale Components Based on a Multiple Field of View Combination

Considering the limited measurement range of a machine vision method for the three-dimensional (3D) surface measurement of large-scale components, a noncontact and flexible global measurement method combining a multiple field of view (FOV) is proposed in this paper. The measurement system consists of two theodolites and a binocular vision system with a transfer mark. The process of multiple FOV combinations is described, and a new global calibration method is proposed to solve the coordinate system unification issue of different instruments in the measurement system. In addition, a high-precision image acquisition method, which is based on laser stripe scanning and centre line extraction, is discussed to guarantee the measurement efficiency. With the measured 3D data, surface reconstruction of large-scale components is accomplished by data integration. Experiments are also conducted to verify the precision and effectiveness of the global measurement method.

结合分层处理的激光光条亚像素中心提取方法

A sub-pixel center extraction algorithm based on hierarchical processing was proposed for the implementation of laser stripe processing in the large aerospace parts measurement with high speed and precision. Firstly, the high-resolution image was compressed into low-resolution image with structural invariance. Then, the normal vector of the center of laser stripe was calculated by using quadratic curve fitting in the low-resolution image. The normal vector in the low-resolution image was reproduced to the high-resolution image based on the theory of normal regression. The judgment of gray center on normal direction was established to determine calculated pixels. The sub-pixel center of calculated pixels on the normal direction was accurately calculated by the gray weighted centroid method. Finally, the presented method was utilized to measure a composite material standard part and complex aviation parts in the laboratory and assembly testing machine, respectively. Experimental results show that the precision of the reconstruction of a single stripe on the surface of object is 0.269 mm and the precision of three-dimension surface measurement is 0.268 mm. It indicates that the proposed method can improve the speed and precision of the engineering measurement of large part. Moreover, the method can satisfy the requirements of the in-site measurement of large aerial parts.

A Measurement Method for Large Parts Combining with Feature Compression Extraction and Directed Edge-Point Criterion

High-accuracy surface measurement of large aviation parts is a significant guarantee of aircraft assembly with high quality. The result of boundary measurement is a significant parameter for aviation-part measurement. This paper proposes a measurement method for accurately measuring the surface and boundary of aviation part with feature compression extraction and directed edge-point criterion. To improve the measurement accuracy of both the surface and boundary of large parts, extraction method of global boundary and feature analysis of local stripe are combined. The center feature of laser stripe is obtained with high accuracy and less calculation using a sub-pixel centroid extraction method based on compress processing. This method consists of a compressing process of images and judgment criterion of laser stripe centers. An edge-point extraction method based on directed arc-length criterion is proposed to obtain accurate boundary. Finally, a high-precision reconstruction of aerospace part is achieved. Experiments are performed both in a laboratory and an industrial field. The physical measurements validate that the mean distance deviation of the proposed method is 0.47 mm. The results of the field experimentation show the validity of the proposed method.

An Improved Method of Contour Extraction of Complex Stripe in 3D Laser Scanning

The contour extraction of laser strip is the most critical part of the 3D measurement based on line-structured laser scanning, and its accuracy and robustness directly affects the performance of the system. For the problem that the width of the stripe changes with orientation or reflectivity on the surface, an improved self-adaptive extraction methods is proposed based on Steger's algorithm. In this method, a fixed scale is firstly chosen according to the width of laser beam to convolute the image with Gaussian kernels and get the hessian matrix of every point, then calculate the width along normal direction. The contour of the complex stripes is extracted with sub-pixel accuracy by combing the character that the second derivative takes different extremums for different width under fixed scale space. The validity and superiority of the method are tested separately and the results show excellent performance on extracting the precise contour of complex strips with variable width.

Timed evaluation of the center extraction of a moving laser stripe on a vehicle body using the Sigmoid-Gaussian function and a tracking method

We timed the extraction of a moving laser stripe from a video using the Sigmoid-Gaussian function and the Hessian matrix method. A tracking model using the Kalman filter method was used to analyze the moving laser stripe projected on the vehicle body. The small region of the laser stripe predicted the subsequent frame based on the prior frame. To verify the extraction of the centers and the tracking effects of the moving laser stripe using the Kalman filter method, two videos of a moving laser plane scanning the vehicle body were captured in the experiments. The region including the laser stripe was predicted from the video frames. Moreover, we conducted two comparative experiments that provided 20 frames from the 10th frame to the 200th frame to evaluate the time and time reduction rate of the extraction of the laser stripe centers using this method and without tracking. The mean time reductions of the extraction in the two tests were 24.14% and 32.77%, respectively. Therefore, the time to extract the centers of the laser stripe was quantified using a Sigmoid-Gaussian function and a tracking method.

Above room temperature continuous wave operation of a broad-area quantum-cascade laser

We describe the design and implementation of a broad-area (w ≈ 30 μm) quantum-cascade laser operating in a continuous wave mode up to heat-sink temperatures beyond +100 °C. The room-temperature emission wavelength is 4.6 μm. The temperature gradient in the active region of such a wide laser stripe is essentially perpendicular to the epitaxial layers and the resulting steady-state active region temperature offset scales approximately with the square of the number of cascades. With only 10 cascades in the active region, the threshold electrical power density in the current quantum-cascade laser in the continuous-wave mode is as low as Vth × Ith = 3.8 V × 0.9 kA/cm2 = 3.4 kW/cm2 at room temperature for 2 mm-long two-side high-reflectivity coated laser stripe. A 4 mm-long one-side high-reflectivity coated laser stripe delivers in continuous-wave mode above 0.6 W at +20 °C and above 1.3 W at −27 °C (cooled with a single-stage Peltier element). A 2 mm-long two-side high-reflectivity coated laser stripe demonstrates continuous-wave lasing up to at least +102 °C (375 K). The thermal conductance, Gth, ranges between 235 W/K cm2 and 140 W/K cm2 for temperatures between −33 °C and +102 °C. This demonstration opens the route for continuous-wave power scaling of quantum-cascade lasers via broad-area laser ridges.

A robust butt welding seam finding technique for intelligent robotic welding system using active laser vision

Intelligent robotic welding requires automatic finding of the seam geometrical features in order for an efficient intelligent control. Performance of the system, therefore, heavily depends on the success of the seam finding stage. Among various seam finding techniques, active laser vision is the most effective approach. It typically requires high-quality lasers, camera and optical filters. The success of the algorithm is highly sensitive to the image processing and feature extraction algorithms. In this work, sequential image processing and feature extraction algorithms are proposed to effectively extract the seam geometrical properties from a low-quality laser image captured without the conventional narrow band filter. A novel method of laser segmentation and detection is proposed. The segmentation method involves averaging, colour processing and blob analysis. The detection method is based on a novel median filtering technique that involves enhancing of the image object based on its underlying structure and orientation in the image. The method when applied enhances the vertically oriented laser stripe in the image which improves the laser peak detection. The image processing steps are performed to make sure that the laser profile is accurately extracted within the region of interest (ROI). Feature extraction algorithm based on pixels’ intensity distribution and neighbourhood search is also proposed that can effectively extract the seam feature points. The proposed algorithms have been implemented and evaluated on various background complexities, seam sizes, material type and laser types before and during the welding operation.

A Laser Line Auto-Scanning System for Underwater 3D Reconstruction.

In this study, a laser line auto-scanning system was designed to perform underwater close-range 3D reconstructions with high accuracy and resolution. The system changes the laser plane direction with a galvanometer to perform automatic scanning and obtain continuous laser strips for underwater 3D reconstruction. The system parameters were calibrated with the homography constraints between the target plane and image plane. A cost function was defined to optimize the galvanometer’s rotating axis equation. Compensation was carried out for the refraction of the incident and emitted light at the interface. The accuracy and the spatial measurement capability of the system were tested and analyzed with standard balls under laboratory underwater conditions, and the 3D surface reconstruction for a sealing cover of an underwater instrument was proved to be satisfactory.

3D Model Reconstruction System Development Based on Laser-Vision Technology

We propose a three-dimensional (3D) scanning system based on laser-vision technique and rotary mechanism combination for automatic 3D model reconstruction. The proposed scanning system consists of a laser projector, camera, and turntable. For laser-camera calibration, a new and simple method is applied. The 3D point cloud data of the surface of the scanned object are fully collected by integrating the extracted laser profiles from the laser stripe images corresponding to the rotary angles of the rotary mechanism. The obscured laser profile problem is solved by an additional camera at another viewpoint. From the collected 3D point cloud data, the 3D model of the scanned object is reconstructed based on the facet-representation method. The reconstructed 3D models showed the effectiveness and applicability of the proposed 3D scanning system in many 3D model-based applications.

On-site calibration method for outdoor binocular stereo vision sensors

Using existing calibration methods for binocular stereo vision sensors (BSVS), it is very difficult to extract target characteristic points in outdoor environments under complex light conditions. To solve the problem, an online calibration method for BSVS based a double parallel cylindrical target and a line laser projector is proposed in this paper. The intrinsic parameters of two cameras are calibrated offline. Laser strips on the double parallel cylindrical target are mediated to calibrate the configuration parameters of BSVS. The proposed method only requires images of laser strips on the target and is suitable for the calibration of BSVS in outdoor environments. The effectiveness of the proposed method is validated through physical experiments.

레이저 구조광 영상기반 3차원 스캐너 개발

This paper addresses the development of 3D data acquisition system (3D scanner) based laser structured-light image. The 3D scanner consists of a stripe laser generator, a conventional camera, and a rotation table. The stripe laser onto an object has distortion according to 3D shape of an object. By analyzing the distortion of the laser stripe in a camera image, the scanner obtains a group of 3D point data of the object. A simple semiconductor stripe laser diode is adopted instead of an expensive LCD projector for complex structured-light pattern. The camera has an optical filter to remove illumination noise and improve the performance of the distance measurement. Experimental results show the 3D data acquisition performance of the scanner with less than 0.2㎜ measurement error in 2 minutes. It is possible to reconstruct a 3D shape of an object and to reproduce the object by a commercially available 3D printer.

An improved image acquisition method for measuring hot forgings using machine vision

Machine vision has already been used for measuring the dimensions of hot forgings. However, the features of hot forgings are not sufficiently clear to be extracted robustly and efficiently because of the poor image quality caused by the radiation that the hot forgings emit. Therefore, to obtain clear images, an improved image acquisition method for the measurement of hot forgings using machine vision is proposed in this paper. Firstly, an image evaluation model based on the Signal to Noise Ratio (SNR) of the Region of Interest (ROI) is established. Then, main interference factors that affect the quality of image, such as the forgings radiation light and laser light, are analysed. Next, the compensation parameters for clear image acquisition in spite of time-varying temperature are obtained. Finally, the laboratory experiments indicate that the quality of the forging images with the laser strips is improved effectively. Meanwhile, three hot parts with different heights are measured in laboratory, and the absolute error is less than 0.32mm, the relative error is less than 0.27%. The dimensional measurement of the hot forging in a workshop is also conducted to verify the effectiveness of the presented system.

激光辅助的大型回转类零件直径实时测量方法

A machine vision measurement method for diameters of large rotary parts based on the intersections of laser stripes was proposed to realize o-line and no-contact measurement in industrial field. Combined with geometric constraints, feature information of measurement for diameters was constructed with hig-strength and hig-directivity lasers. Feature points for measurement were emphasized by projecting intersecting laser stripes on the surfaces of large rotary parts. A hig-precision extraction method was proposed based on the distribution character of intersections on the surfaces of large rotary parts. The space coordinates of intersections were reconstructed through calibration results and the diameters can be calculated by modeling the corresponding elliptic. Measurement experiment for diameters was carried out in a laboratory, of which the results show that the measurement error was 0.5%. It provides a reliable technology for o-line and no-contact measurement for large rotary parts.

激光辅助的大型回转类零件直径实时测量方法

A machine vision measurement method for diameters of large rotary parts based on the intersections of laser stripes was proposed to realize o-line and no-contact measurement in industrial field. Combined with geometric constraints, feature information of measurement for diameters was constructed with hig-strength and hig-directivity lasers. Feature points for measurement were emphasized by projecting intersecting laser stripes on the surfaces of large rotary parts. A hig-precision extraction method was proposed based on the distribution character of intersections on the surfaces of large rotary parts. The space coordinates of intersections were reconstructed through calibration results and the diameters can be calculated by modeling the corresponding elliptic. Measurement experiment for diameters was carried out in a laboratory, of which the results show that the measurement error was 0.5%. It provides a reliable technology for o-line and no-contact measurement for large rotary parts.

Extraction of laser stripe subpixel center in highnoise background

Extraction of laser stripe subpixel center in highnoise background