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

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.

Robotic weld groove scanning for large tubular T-joints using a line laser sensor

This paper presents a novel procedure for robotic scanning of weld grooves in large tubular T-joints. The procedure is designed to record the discrete weld groove scans using a commercially available line laser scanner which is attached to the robot end-effector. The advantage of the proposed algorithm is that it does not require any prior knowledge of the joint interface geometry, while only two initial scanning positions have to be specified. The position and orientation of the following scan are calculated using the data from two previous weld groove scans, so once initiated, the scanning process is fully autonomous. The procedure is a two-step algorithm consisting of the prediction and correction substeps, where the position and orientation of the sensor for the following scan are predicted and corrected. Such a procedure does not require frequent weld groove scanning for navigation along the groove. The performance of the proposed procedure is studied experimentally using an industrial-size T-joint specimen. Several cases of scanning motion parameters have been tested, and a discussion on the results is given.publishedVersio

A passive imaging system for geometry measurement for the plasma arc welding process

Automatic and flexible geometry measurement of the weld pool surface can help better understand the complex welding processes and even provide feedback to better control this process. Most of existing imaging systems use an additional source of illumination to remove the light interference coming from the welding arc but it is usually costly. This paper introduces a novel low-cost optical-sensor-based monitoring system working under passive mode to monitor the wire + arc additive manufacture (WAAM) process, particularly for plasma arc welding. Initially, configurations and parameters of camera are investigated to achieve good visualisation of weld pool. A novel camera calibration methodology using the nozzle of a CNC machine is then proposed for this imaging system allowing estimation of the camera position with respect to the inspecting surface and its orientation in an easy-to-use approach. The verification tests show that the average error of the calibration is less than 1 pixel. As a case study, an image analysis routine is proposed to measure the width of the bead during the welding process. The results show that the proposed system is effective to measure the dimension of weld pool

Robotics in space-age manufacturing

Robotics technologies are developed to improve manufacturing of space hardware. The following applications of robotics are covered: (1) welding for the space shuttle and space station Freedom programs; (2) manipulation of high-pressure water for shuttle solid rocket booster refurbishment; (3) automating the application of insulation materials; (4) precision application of sealants; and (5) automation of inspection procedures. Commercial robots are used for these development programs, but they are teamed with advanced sensors, process controls, and computer simulation to form highly productive manufacturing systems. Many of the technologies are also being actively pursued in private sector manufacturing operations

Machine-human Cooperative Control of Welding Process

An innovative auxiliary control system is developed to cooperate with an unskilled welder in a manual GTAW in order to obtain a consistent welding performance. In the proposed system, a novel mobile sensing system is developed to non-intrusively monitor a manual GTAW by measuring three-dimensional (3D) weld pool surface. Specifically, a miniature structured-light laser amounted on torch projects a dot matrix pattern on weld pool surface during the process; Reflected by the weld pool surface, the laser pattern is intercepted by and imaged on the helmet glass, and recorded by a compact camera on it. Deformed reflection pattern contains the geometry information of weld pool, thus is utilized to reconstruct its $3$D surface. An innovative image processing algorithm and a reconstruction scheme have been developed for (3D) reconstruction. The real-time spatial relations of the torch and the helmet is formulated during welding. Two miniature wireless inertial measurement units (WIMU) are mounted on the torch and the helmet, respectively, to detect their rotation rates and accelerations. A quaternion based unscented Kalman filter (UKF) has been designed to estimate the helmet/torch orientations based on the data from the WIMUs. The distance between the torch and the helmet is measured using an extra structure-light low power laser pattern. Furthermore, human welder\u27s behavior in welding performance has been studied, e.g., a welder`s adjustments on welding current were modeled as response to characteristic parameters of the three-dimensional weld pool surface. This response model as a controller is implemented both automatic and manual gas tungsten arc welding process to maintain a consistent full penetration

On Sensor-Controlled Robotized One-off Manufacturing

A semi-automatic task oriented system structure has been developed and tested on an arc welding application. In normal industrial robot programming, the path is created and the process is based upon the decided path. Here a process-oriented method is proposed instead. It is natural to focus on the process, since the path is in reality a result of process needs. Another benefit of choosing process focus, is that it automatically leads us into task oriented thoughts, which in turn can be split in sub-tasks, one for each part of the process with similar process-characteristics. By carefully choosing and encapsulating the information needed to execute a sub-task, this component can be re-used whenever the actual subtask occurs. By using virtual sensors and generic interfaces to robots and sensors, applications built upon the system design do not change between simulation and actual shop floor runs. The system allows a mix of real- and simulated components during simulation and run-time