Applications of laser transmission processes for the joining of plastics, silicon and glass micro parts

Joining processes for microtechnology must fulfil special requirements concerning mechanical and thermal load of the components as well as their alignment accuracy. For these applications laser radiation as an energy source is ideally suited for joining with a minimum of energy load to the parts. In particular, laser transmission joining is used for joining plastics, silicon or glass using the total or partial transmission of the different materials and performing hidden joints inside a component. Since the optical properties of the materials play a decisive role for this joining technology, an optimization of absorbers and material conditions is of crucial importance for high quality joints. Investigations on different absorbent dyes for micro welding of plastics show their applicability, but also the limitations of these materials. For silicon and glass as well as silicon and silicon new fiber lasers with process-adapted wavelengths and strategies have been investigated and qualified as a versatile tool in micro assembly.     

色噪声下卡尔曼滤波焊缝跟踪算法与试验研究

精确控制激光束使其始终对中并跟踪焊缝是保证激光焊接质量的前提．以大功率光纤激光焊接Type304不锈钢为试验对象,研究一种有色噪声环境下应用卡尔曼滤波最优状态估计预测激光束与焊缝路径偏差的方法．使用高速红外视觉传感器摄取焊接区红外热像,提取焊缝位置参数并构成状态向量,建立基于焊缝位置参数的系统状态方程和焊缝位置测量方程．针对系统动态噪声为有色噪声,通过扩展状态变量的方法建立有色噪声环境下的卡尔曼滤波算法,对焊缝位置进行最优状态估计并得到最小均方差条件下的焊缝偏差最优预测值,消除系统噪声对焊缝偏差测量的影响．焊接试验结果表明新方法可有效抑制有色噪声干扰并提高焊缝跟踪精度．     

A robust weld seam recognition method under heavy noise based on structured-light vision

Structured-light vision systems are widely used in robotic welding. The key to improving the robotic visual servo performance and weld quality is the weld seam recognition accuracy. Common detection algorithms are likely to be disturbed by the noise of spatter and arc during the welding process. In this paper, a weld seam recognition algorithm is proposed based on structured light vision to overcome this challenge. The core of this method is fully utilizing information of previous frames to process the current frame, which can make weld seam extraction both more robust and effective. The algorithm can be divided into three steps: initial laser center line recognition, online laser center line detection, and weld feature extraction. A Laplacian of Gaussian filter is used for recognizing the laser center line in the first frame. Afterwards, an algorithm based on the NURBS-snake model detects the laser center line online in a dynamic region of interest (abbreviated ROI). The center line obtained from first step is set as the initial contour of the NURBS-snake model. Using the line obtained from the previous step, feature points are determined by segmentation and straight-line fitting, while the position of the weld seam can be calculated according to the feature points. The accuracy, efficiency and robustness of the recognition algorithm are verified by experiments.     

High aspect ratio structures obtained by electroforming in microstructured glass

 The application of glass in the microsystems technology becomes more and more important. Therefore, it is necessary to combine special microstructurable glasses with various other materials (e.g. joining with silicon by anodic bonding, joining with metals by electroforming, joining with polymers by glueing, joining with various other glasses by brazing or diffusion welding). In order to increase the use of glass in the microsystems technology especially four fields of research are important: –development of special glasses with various properties –technologies of microstructuring –technologies of joining –application These four topics are main research fields performed at the Institute of Glass/Ceramics-Technology and will be described in this paper. Received: 30 October 1995 / Accepted: 12 January 1996     

卡尔曼滤波焊缝跟踪控制

在视觉传感的电弧自动焊接过程中,需要根据视觉信息来控制电弧准确地跟踪焊缝.由于强烈的弧光干扰,使得从焊接区图像中直接提取电弧与焊缝的偏差信息十分困难.为此提出一种利用熔池图像质心和卡尔曼滤波来间接获取电弧与焊缝偏差的方法.选择熔池图像质心作为状态向量,建立基于图像质心的状态方程和焊缝位置测量方程.利用卡尔曼滤波消除过程噪声和测量噪声的影响,通过对熔池图像质心的状态估计,准确获取焊缝位置以及电弧与焊缝之间的偏差量,为自动焊接过程的焊缝跟踪控制提供准确信息.焊接试验结果表明,利用卡尔曼滤波方法可有效降低过程噪声和测量噪声的影响,从而提高焊缝跟踪控制精度.     

Weld seam profile detection and feature point extraction for multi-pass route planning based on visual attention model

Automatic multi-pass route planning is one of key technologies for thick plate in robotic metal active gas (MAG) arc welding. In this research, a scheme for the extracting feature points of the weld seam profile to implement automatic multi-pass route planning, and guidance of the initial welding position in each layer during MAG arc welding, is presented. It consists of two steps: first a vision sensor based on structured light is employed to capture laser stripes and molten pools simultaneously within the same frame, and the laser stripe, forming the weld seam profile is detected by a visual attention model based on saliency. Then a methodology of polynomial fitting plus derivatives for feature point extraction of the weld seam profile is suggested. With respect to the effectiveness of highlighting the laser stripe, the proposed model is much better than the classic ones in this field, whereas the feature point extraction methodology in this paper outperforms typical template matching. Finally, the performance of the proposed scheme is demonstrated on different weld seam images captured in different layers and different welding experiments.     

High aspect ratio structures obtained by electroforming in microstructured glass

The application of glass in the microsystems technology becomes more and more important. Therefore, it is necessary to combine special microstrutturable glasses with various other materials (e.g. joining with silicon by anodic bonding, joining with metals by electroforming, joining with polymers by glueing, joining with various other glasses by brazing or diffusion welding). In order to increase the use of glass in the microsystems technology especially four fields of research are important:

-development of special glasses with various properties

-technologies of microstructuring

-technologies of joining

-application

These four topics are main research fields performed at the Institute of Glass/Ceramics-Technology and will be described in this paper.     

Characterization of localized laser assisted eutectic bonds

An innovative bonding process for silicon and single crystal quartz has been developed and investigated using various material science characterization methods, such as TOF-SIMS, SEM, EDX and XRD. The bonding process combines the principles of laser transmission welding, eutectic bonding and bonding by localized heating. A focused laser beam (low power, max. 0.83 W) is transmitted through a quartz medium to intermediate layers of chromium, gold and tin at the silicon–quartz interface to provide localized heating and bonding. This bonding process is particularly suitable for bonding wafers containing temperature sensitive devices as it confines the temperature increase to a small area. Bond strength of over 15 MPa is comparable to most localized bonding schemes. This process provides a simple yet robust bonding solution with rapid processing time, selectivity of bonded area and corrosion resistant joints.     

Autonomous Detection of Weld Seam Profiles via a Model of Saliency-Based Visual Attention for Robotic Arc Welding

This paper presents a method of autonomously detecting weld seam profiles from molten pool background in metal active gas (MAG) arc welding using a novel model of saliency-based visual attention. First, a vision sensor based on structured light is employed to capture laser stripes and molten pools simultaneously in the same frame. Second, to effectively detect the weld seam profile from molten pool background for next autonomous guidance of initial welding positions and seam tracking, a model of visual attention based on saliency is proposed. With respect to the enhanced effect of saliency, the proposed model is much better than the classic models in the field. According to the comprehensive saliency map created by the proposed model, the weld seam profile can be extracted after threshold segmentation and clustering are applied to it in turn. Third, different weld seam images are used to demonstrate the robustness of the proposed methodology and last, to evaluate the performance of the proposed method, a measure called profile extraction rate (PER) is computed, which shows that the extracted weld seam profile can basically meet the requirements of seam tracking and the guidance of welding torches.     

经济型焊缝跟踪视觉传感器的研制

利用普通的焊接护目镜玻璃制作了熔池图像视觉传感器,在304#不锈钢等离子弧焊缝跟踪试验中获得的图像是足够清晰的,能够清楚地看到接缝和焊接熔池.在工厂车间里进行的试验证明:这种低成本的视觉传感器可以用于304#不锈钢的等离子弧焊接过程的实时焊缝跟踪和控制.     

基于宏微机器人的焊缝跟踪研究

提出了一种基于宏微运动机器人的焊缝跟踪方法．首先,通过若干点的简单示教获得焊缝位置信息,并通过拟合建立焊缝模型．在该模型的基础上,对机器人的宏动进行运动规划．采用激光结构光视觉测量焊缝坐标,并根据焊缝图像偏差控制机器人的微动．结合机器人的宏动规划运动和微动自动调整,实现大范围、高精度的焊缝跟踪．利用宏微运动平台进行了焊缝跟踪实验,实验结果验证了所提出方法的有效性．     

轮辋与轮辐间焊缝参数对钢制车轮弯曲应力影响的仿真分析

为考察轮辋与轮辐间焊缝对钢制车轮强度的影响,建立包括该焊缝在内的钢制车轮的有限元模型,分析在弯曲载荷作用下,钢制车轮轮辋与轮辐间的焊脚高度、焊缝截面形状以及焊缝布置位置对车轮应力的影响．仿真结果表明：对于该钢制车轮,轮辋与轮辐间焊脚高度可以由目前的3.5mm减至2.5mm,这为焊接工艺参数的调整提供一定参考;焊缝截面边界为直边时焊缝处应力较小;当每段焊缝的一半对着通风孔时焊接区域应力较小．该仿真分析可用于钢制车轮轮辋与轮辐间焊缝结构的优化,并为钢制车轮在弯曲载荷作用下的疲劳寿命估算提供更准确的应力计算结果．     

Application of sensing techniques and artificial intelligence-based methods to laser welding real-time monitoring: A critical review of recent literature

Laser welding has been widely utilized in various industries. Effective real-time monitoring technologies are critical for improving welding efficiency and guaranteeing the quality of joint-products. In this paper, the research findings and progress in recent ten years for real-time monitoring of laser welding are critically reviewed. Firstly, different sensing techniques applied for welding quality monitoring are reviewed and discussed in detail. Then, the advanced technologies based on artificial intelligence are summarized which are exploited to realize varied objectives of monitoring such as process parameter optimization, weld seam tracking, weld defects classification, and process feedback control. Finally, the potential research problems and challenges based on real-time intelligent monitoring are discussed, such as intelligent multi-sensor signal acquisition platform, data depth fusion method and adaptive control technology. This fundamental work aims to review the research progress in laser welding monitoring and provide a basis for follow-on research.     

Numerical simulation of the electron beam welding process

Electron beam welding is a highly efficient and precise welding method that is being increasingly used in industrial manufacturing and is of growing importance in industry. Compared to other welding processes it offers the advantage of very low heat input to the weld, resulting in low distortion in components. Modeling and simulation of the laser beam welding process has proven to be highly efficient for research, design development and production engineering. In comparison with experimental studies, a modeling study can give detailed information concerning the characteristics of weld pool and their relationship with the welding process parameters (welding speed, electron beam power, workpiece thickness, etc.) and can be used to reduce the costs of experiments. A simulation of the electron beam welding process enables estimation of weld pool geometry, transient temperature, stresses, residual stresses and distortion. However this simulation is not an easy task since it involves the interaction of thermal, mechanical and metallurgical phenomena. Understanding the heat process of welding is important for the analysis of welding structure, mechanics, microstructure and controlling weld quality.In this paper the results of numerical simulation of electron beam welding of tubes were presented. The tubes were made of 30HGSA steel. The numerical calculation takes into consideration thermomechanical coupling (TMC). The simulation aims at: analysis of the thermal field, which is generated in welding process, determination of the heat-affected zone and residual stresses in the joint. The obtained results allow for determination both the material properties, and stress and strain state in the joint. Furthermore, numerical simulation allows for optimization of the process parameters (welding speed, power of the heat source) and shape of the joint before welding. The numerical simulation of electron beam welding process was carried out with the ADINA System v. 8.6. using finite element method.     

自动控制在薄板钛合金激光焊接中的应用

采用YAG激光作为焊接热源,针对具有自动控制的激光焊接系统,研究了1.3mm厚的TC4钛合金薄板的双面激光焊接.分析了试样的焊前清洗、保护气体的选择及激光工艺参数(激光功率密度、焊接速度、脉冲宽度、频率等)的匹配对焊缝形成及表观形貌的影响.试验结果表明,施焊前对试样进行合适的清洗十分必要,未经清洗的试样很难实现焊接成功.在保护气体的选择方面,使用氩气的焊接效果明显优于使用氮气;激光功率密度、焊接速度、脉冲宽度和脉冲频率4个参数的合理组合,是实现钛合金薄板焊接的关键因素.     

超声波传感器在直角焊缝自动焊接中的应用

机器人进行船体格子型焊缝焊接过程中,完全依靠电弧传感器无法完全得到其周围环境信息,造成了自动化焊接的困难。设计了一种直角焊缝自动焊接的方法,利用超声波传感器代替机械式传感器,获得周围障碍信息,用电弧传感器获得焊缝的偏差信息,通过对机器人合理的控制,完成了直角焊缝的自动跟踪焊接。     

基于视觉与电弧多信息传感的焊缝跟踪算法

随着焊接传感技术以及信号处理技术的快速发展,人们越来越注重对焊接过程质量控制的研究,而多传感器信息融合技术是焊接质量控制的一种重要的方法,采用该技术实现熔化极气体保护焊(MIG)脉冲焊接质量的自动控制。该技术采用了视觉传感器和电弧传感器将采集的不同的描述信息进行了有效的特征提取和传输,并运用多传感器信息融合算法进行焊缝的跟踪。视觉传感器利用工业电荷耦合元件(CCD)获取图像信息控制焊炬的横向偏差信息,电弧传感器利用数据采集卡获取电流信息控制焊炬的高度互补偏差信息和横向的冗余信息,将两种传感器得到的冗余信息和互补信息在特征层下进行融合实现焊接过程横向和高度的纠偏控制。冗余信息的融合可以实现视觉传感的图像去噪,而互补信息的融合可以进一步提高焊缝跟踪的精度。实验结果表明,所提算法能够较好地提高焊接的质量,从而也验证了算法的有效性和合理性。     

Laser transmission bonding of silicon to silicon with metallic interlayers for wafer-level packaging

For packaging of silicon components with low thermal load and high spatial selectivity laser transmission bonding (LTB) of silicon–silicon compounds with intermediate layers using a cw-thulium fiber laser (wavelength 1,940 nm) is investigated. The intermediate layer combination titanium and gold is examined with respect to the bond characteristics and the achievable mechanical properties of the bonded specimens. The tensile strength is measured by using tensile test. Similar specimens bonded with corresponding standard bond process using the same bond geometry are also analyzed in order to compare the measurements.     

Computer vision technology for seam tracking in robotic GTAW and GMAW

Due to ever increasing demand in precision in robotic welding automation and its inherent technical difficulties, seam tracking has become the research hotspot. This paper introduces the research in application of computer vision technology for real-time seam tracking in robotic gas tungsten arc welding (GTAW) and gas metal arc welding (GMAW). The key aspect in using vision techniques to track welding seams is to acquire clear real-time weld images and to process them accurately. This is directly related to the precision of seam tracking. In order to further improve the accuracy of seam tracking, in this paper, a set of special vision system has been designed firstly, which can acquire clear and steady real-time weld images. By analyzing the features of weld images, a new and improved edge detection algorithm was proposed to detect the edges in weld images, and more accurately extract the seam and pool characteristic parameters. The image processing precision was verified through the experiments. Results showed that the precision of this vision based tracking technology can be controlled to be within ±0.17 mm and ±0.3 mm in robotic GTAW and GMAW, respectively.     

Acquisition of Weld Seam Dimensional Position Information for Arc Welding Robot Based on Vision Computing

Recognition and identification of weld environment and seam dimensional position by computer vision is a key technology for developing advanced autonomous welding robot. Aiming at requirements for recognition of weld seam image characteristics, this paper first presents an improved algorithm of subpixel edge detection based on Zernike moments. Comparing with the Ghosal’s original algorithm, the improved algorithm deals with mask effect and first derivative model on edge gradient direction so that it has the strong robust to noise, self-thinning ability and higher locating precision. An algorithm based on ZMs to extract line is also proposed, the comparative results with SHT and RHT show the method has the highest calculation speed and accuracy. The stereovision technology is developed to identify dimensional position of weld seam by computing dimensional coordinates of the weld seam. According to characteristics of weld seam, view field scope model and stereovision model based on baseline are studied and a stereo matching method is presented. In order to evaluate the algorithms and models presented in this paper, a welding robot systems with single camera fixed on the weld torch end-effector has been established for the robot to identify the dimensional position of typical weld seam by one-item and two-position method. The experiment results on S-shape and saddle-shape weld seams show that the vision computing method developed in this paper can be used for acquiring weld seam dimensional position information in welding robot system. Thus the welding path is mapped before the welding operation is executed.