Integrated sensors for robotic laser welding

A welding head is under development with integrated sensory systems for robotic laser welding applications. Robotic laser welding requires sensory systems that are capable to accurately guide the welding head over a seam in three-dimensional space and provide information about the welding process as well as the quality of the welding result. In this paper the focus is on seam tracking. It is difficult to measure three-dimensional parameters of a ream during a robotic laser welding task, especially when sharp corners are present. The proposed sensory system is capable to provide the three dimensional parameters of a seam in one measurement and guide robots over sharp corners

Sensor integration for robotic laser welding processes

The use of robotic laser welding is increasing among industrial applications, because of its ability to weld objects in three dimensions. Robotic laser welding involves three sub-processes: seam detection and tracking, welding process control, and weld seam inspection. Usually, for each sub-process, a separate sensory system is required. The use of separate sensory systems leads to heavy and bulky tools, in contrast to compact and light sensory systems that are needed to reach sufficient accuracy and accessibility. In the solution presented in this paper all three subprocesses are integrated in one compact multipurpose welding head. This multi-purpose tool is under development and consists of a laser welding head, with integrated sensors for seam detection and inspection, while also carrying interfaces for process control. It can provide the relative position of the tool and the work piece in three-dimensional space. Additionally, it can cope with the occurrence of sharp corners along a three-dimensional weld path, which are difficult to detect and weld with conventional equipment due to measurement errors and robot dynamics. In this paper the process of seam detection will be mainly elaborated

High-resolution 3D weld toe stress analysis and ACPD method for weld toe fatigue crack initiation

Weld toe fatigue crack initiation is highly dependent on the local weld toe stress-concentrating geometry including any inherent flaws. These flaws are responsible for premature fatigue crack initiation (FCI) and must be minimised to maximise the fatigue life of a welded joint. In this work, a data-rich methodology has been developed to capture the true weld toe geometry and resulting local weld toe stress-field and relate this to the FCI life of a steel arc-welded joint. To obtain FCI lives, interrupted fatigue test was performed on the welded joint monitored by a novel multi-probe array of alternating current potential drop (ACPD) probes across the weld toe. This setup enabled the FCI sites to be located and the FCI life to be determined and gave an indication of early fatigue crack propagation rates. To understand fully the local weld toe stress-field, high-resolution (5 mu m) 3D linear-elastic finite element (FE) models were generated from X-ray micro-computed tomography (mu-CT) of each weld toe after fatigue testing. From these models, approximately 202 stress concentration factors (SCFs) were computed for every 1 mm of weld toe. These two novel methodologies successfully link to provide an assessment of the weld quality and this is correlated with the fatigue performance

Measurement of local creep properties in stainless steel welds

A high temperature measurement system for creep deformation based on the digital image correlation (DIC) technique is described. The new system is applied to study the behaviour of a multi-pass welded joint in a high temperature tensile test and a load controlled creep test at 545°C. Spatially resolved tensile properties and time dependent creep deformation properties across a thick section type 316 stainless steel multi-pass welded joint are presented and discussed. Significantly lower creep strain rates are observed in the HAZ than in the parent material which is attributed to the introduction of substantial plastic strain in the parent material on initial loading. The weld metal shows the fastest creep rates and a variation that appear to correlate with individual weld passes. The visual information provides not only the local creep strain distribution but also the reduction of area and true stress distribution based on strains measured in the transverse direction. The results demonstrate the capability of the DIC technique for full field measurement of displacement and strain at high temperature long term creep tests

Visual Sensing and Defect Detection of Gas Tungsten Arc Welding

Weld imperfections or defects such as incomplete penetration and lack of fusion are critical issues that affect the integration of welding components. The molten weld pool geometry is the major source of information related to the formation of these defects. In this dissertation, a new visual sensing system has been designed and set up to obtain weld pool images during GTAW. The weld pool dynamical behavior can be monitored using both active and passive vision method with the interference of arc light in the image significantly reduced through the narrow band pass filter and laser based auxiliary light source.Computer vision algorithms based on passive vision images were developed to measure the 3D weld pool surface geometry in real time. Specifically, a new method based on the reversed electrode image (REI) was developed to calculate weld pool surface height in real time. Meanwhile, the 2D weld pool boundary was extracted with landmarks detection algorithms. The method was verified with bead-on-plate and butt-joint welding experiments.Supervised machine learning was used to develop the capability to predict, in real-time, the incomplete penetration on thin SS304 plate with the key features extracted from weld pool images. An integrated self-adaptive close loop control system consisting the non-contact visual sensor, machine learning based defect predictor, and welding power source was developed for real-time welding penetration control for bead on plate welding. Moreover, the data driven methods were first applied to detect incomplete penetration and LOF in multi-pass U groove welding. New features extracted from reversed electrode image played the most important role to predict these defects. Finally, real time welding experiments were conducted to verify the feasibility of the developed models

Advances in Plasma Arc Welding: A Review

The nature of welding in the aeronautical industry is characterized by low unit production, high unit cost, extreme reliability and severe service conditions. These characteristics point towards more expensive and more concentrated heat sources such as plasma arc, laser beam and electron beam welding as the processes of choice for welding of critical components. Among various precision welding processes, Plasma Arc welding has gained importance in small and medium scale industries manufacturing bellows , diaphragms etc because of less expensive and easy to operate. This paper reviews the works on Plasma Arc welding and associated phenomena such as Micro Plasma Arc Welding, Variable Polarity Plasma Arc welding and Keyhole Plasma Arc Welding. The review covers works carried out by various researchers on various metals using different modes of plasma arc

Intelligent 3D seam tracking and adaptable weld process control for robotic TIG welding

Tungsten Inert Gas (TIG) welding is extensively used in aerospace applications, due to its unique ability to produce higher quality welds compared to other shielded arc welding types. However, most TIG welding is performed manually and has not achieved the levels of automation that other welding techniques have. This is mostly attributed to the lack of process knowledge and adaptability to complexities, such as mismatches due to part fit-up. Recent advances in automation have enabled the use of industrial robots for complex tasks that require intelligent decision making, predominantly through sensors. Applications such as TIG welding of aerospace components require tight tolerances and need intelligent decision making capability to accommodate any unexpected variation and to carry out welding of complex geometries. Such decision making procedures must be based on the feedback about the weld profile geometry. In this thesis, a real-time position based closed loop system was developed with a six axis industrial robot (KUKA KR 16) and a laser triangulation based sensor (Micro-Epsilon Scan control 2900-25). [Continues.

Index to 1981 NASA Tech Briefs, volume 6, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1981 Tech Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

A Laser-Based Vision System for Weld Quality Inspection

Welding is a very complex process in which the final weld quality can be affected by many process parameters. In order to inspect the weld quality and detect the presence of various weld defects, different methods and systems are studied and developed. In this paper, a laser-based vision system is developed for non-destructive weld quality inspection. The vision sensor is designed based on the principle of laser triangulation. By processing the images acquired from the vision sensor, the geometrical features of the weld can be obtained. Through the visual analysis of the acquired 3D profiles of the weld, the presences as well as the positions and sizes of the weld defects can be accurately identified and therefore, the non-destructive weld quality inspection can be achieved

Local threshold identification and gray level classification of butt joint welding imperfections using robot vision system

This research is carried out be able to automatically identify the joint position and classify the quality level of imperfections for butt welding joint based on background subtraction, local thresholding and gray level approaches without any prior knowledge of the joint shapes. The background subtraction and local thresholding approaches consist of image pre-processing, noise reduction and butt welding representation algorithms. The approaches can automatically recognize and locate the butt joint position of the starting, middle, auxiliary and ending point according to the three different joint shapes; straight line, tooth saw and curved joint shapes. The welding process was done by implemented an automatic coordinate conversion between camera (pixels) and KUKA welding robot coordinate (millimeters) from the KUKA welding robot and camera coordinate ratio. The ratio was determined by a camera and three reference point (origin, x-direction and y-direction) taken around workpiece. Hence, the quality level of imperfection for butt welding joint was classified using Gaussian Mix Model (GMM), Multi-Layer Perceptron (MLP) and Support Vector Machine (SVM) classifiers according to their class of imperfection categories; good welds, excess welds, insufficient welds and no weld in each welding joint shape. These classifiers introduced 72 characteristics of feature values of gray pixels taken from co-occurrence matrix. The feature values consist of energy, correlation, homogeneity and contrast combine with gray absolute histogram of edge amplitude including additional characteristic features with scaled image factor by 0.5. The proposed approaches were validated through experiments with a KUKA welding robot in a realistic workshop environment. The results show that the approaches introduced in this research can detect, identify, recognize, locate the welding position and classify the quality level of imperfections for butt welding joint automatically without any prior knowledge of the joint shapes