YuMing Zhang

Weld deposition-based rapid prototyping: a preliminary study

Abstract At the present time, the most widely used commercial rapid prototyping (RP) processes are based on polymeric materials, such as plastics or photocurable resins. While these prototype products adequately meet the requirements for “form” and “fit”, they are only very infrequently able to provide any “function” capability. This is especially true when considering metallic products. Laser sintering of metal powers has been studied and is currently being developed into a viable process. However, laser sintering requires expensive equipment and a high price form of starting material. A possibly more economical alternative is offered by the use of weld deposition processing. Research at the University of Kentucky has allowed the development of a dedicated control technology, including slicing/planning, system implementation and post-processing for RP using gas metal arc welding as the deposition process. The metal transfer control system is used to control the size and frequency of the droplets in order to improve the deposition accuracy. The component to be prototyped is specified by CAD surfaces or a solid model in standard IGES format. An integrated and user-friendly environment has been developed to slice the part, plan the deposition parameters, and control the deposition process. In this system, the deposition parameters, and control the deposition process. In this system, the deposition parameters, including the travel speed, touch angle, welding current, and arc voltage, are variably controlled to achieve the required density and three-dimensional geometry. This system, together with its operation, is destroyed and examples of several complex-shaped components produced are illustrated.

Sensing and Control of Weld Pool Geometry for Automated GTA Welding

Weld pool geometry is a crucial factor in determining welding quality, especially in the case of sheet welding. Its feedback control should be a fundamental requirement for automated welding. However, the real-time precise measurement of pool geometry is a difficult procedure. It has been shown that vision sensing is a promising approach for monitoring the weld pool geometry. Quality images that can be processed in real-time to detect the pool geometry are acquired by using a high shutter speed camera assisted with nitrogen laser as an illumination source. However, during practical welding, impurities or oxides existing on the pool surface complicate image processing. The image features are analyzed and utilized for effectively processing the image. It is shown that the proposed algorithm can always detect the pool boundary with sufficient accuracy in less than 100 ms. Based on this measuring technique, a robust adaptive system has been developed to control the pool area. Experiments show that the proposed control system can overcome the influence caused by various disturbances.

Real-Time Image Processing for Monitoring of Free Weld Pool Surface

The arc weld pool is always deformed by plasma jet. In a previous study, a novel sensing mechanism was proposed to sense the free weld pool surface. The specular reflection of pulsed laser stripes from the mirror-like pool surface was captured by a CCD camera. The distorted laser stripes clearly depicted the 3D shape of the free pool surface. To monitor and control the welding process, the on-line acquisition of the reflection pattern is required. In this work, the captured image is analyzed to identify the torch and electrode. The weld pool edges are then detected. Because of the interference of the torch and electrode, the acquired pool boundary may be incomplete. To acquire the complete pool boundary, models have been fitted using the edge points. Finally, the stripes reflected from the weld pool are detected. Currently, the reflection pattern and pool boundary are being related to the weld penetration and used to control the weld penetration.

Automated system for welding-based rapid prototyping

Abstract The manufacturing of “form-fit-function” components, rather than just “form/fit” parts, is currently a major issue in rapid prototyping (RP). As a deposition process, gas metal arc welding (GMAW) has shown promise for RP of metallic parts. In current RP systems, slicing and planning are done based on STL files, and system implementation and post-processing are designed according to the deposition processes used. Due to the significant difference between the welding process and the existing deposition processes, the authors have developed a dedicated technology, including slicing/planning, system implementation, and post-processing for RP using GMAW as the deposition process. For form-fit-and-function testing, a special RP system, including software and hardware, is developed. This system is capable of handling tolerance specifications and material properties. A novel metal transfer control technology is used to precisely control the size and frequency of the droplet in order to improve the deposition accuracy. The part to be prototyped is given by a CAD surface or a solid model in the standard IGES format. A friendly and integrated environment, referred to as welding deposition wizard (WDW), has been developed to slice the part, plan the deposition parameters, and control the deposition process. Test results show that the system can process various models in IGES format with general entities. The model is sliced according to a comprehensive survey of the tolerance, the speed, and the implementation feasibility. The minimization of ignition times, the ignition control, and the crater filling control are incorporated in the planning algorithm for deposition parameters. The slicing and planning algorithm also optimizes the transition from interior to outline pass. The planned deposition parameters ensure the required density and deposition height are achieved. In current RP systems, the deposition parameters, for example, the intensity and travel speed of the laser beam in Stereolithography, are constant. In the developed system, the deposition parameters, including the travel speed, torch angle, welding current, and arc voltage, are changed to achieve the required density and geometry. Unlike current STL-based approximation algorithms, the outline of each layer is deposited with vector motions to obtain the original geometry of the part. The interior is filled with a raster fill pattern to obtain a high deposition speed.

Robust sensing of arc length

During arc welding, the arc heats and melts the workpiece as heat flux. When the welding current is given, the distribution and the intensity of the heat flux are determined by the length of the are. The measurement and control of the are length are fundamental in robotic and automated welding operations. Length of welding arc determines the distribution of the arc energy and thus the heat input and width of the weld. This work aims at improving the measurement accuracy of arc length using the spectrum of are light at a particular wavelength during gas tungsten arc welding (GTAW) with argon shield. To this end, effects of welding parameters on spectral distributions were studied. To verify the effects of base metal and arc length, the arc column was also sampled horizontally as Layers for spectral analysis. Results show that spectral lines of argon atoms are determined by are length, independent of welding parameters other than the current. Based on these findings, a compact arc light sensor has been designed to measure the arc length with adequate accuracy. A closed-loop arc length control system has been developed with the proposed sensor.

Dynamic Neuro-Fuzzy-Based Human Intelligence Modeling and Control in GTAW

Human welders experiences and skills are critical for producing quality welds in manual gas tungsten arc welding (GTAW) process. In this paper, a neuro-fuzzy-based human intelligence model is constructed and implemented as an intelligent controller in automated GTAW process to maintain a consistent desired full penetration. An innovative vision system is utilized to real-time measure the specular 3D weld pool surface under strong arc light interference. Experiments are designed to produce random changes in the welding speed and voltage resulting in fluctuations in the weld pool surface. Adaptive neuro-fuzzy inference system (ANFIS) is proposed to correlate the human welders response to the 3D weld pool surface as characterized by its width, length and convexity. Closed-loop control experiments are conducted to verify the robustness of the proposed controller. It is found that the human intelligence model can adjust the current to robustly control the process to a desired penetration state despite different initial conditions and various disturbances. A foundation is thus established to explore the mechanism and transformation of human welders intelligence into robotic welding systems.

Model-Based Predictive Control of Weld Penetration in Gas Tungsten Arc Welding

Skilled welders can estimate and control the weld joint penetration, which is primarily measured by the backside bead width, based on weld pool observation. This suggests that an advanced control system could be developed to control the weld joint penetration by emulating the estimation and decisionmaking process of the human welder. In this paper an innovative 3-D vision sensing system is used to measure the characteristic parameters of the weld pool in real-time in gas tungsten arc welding. The measured characteristic parameters are used to estimate the backside bead width, using an adaptive neuro-fuzzy inference system (ANFIS) as an emulation of skilled welder. Dynamic experiments are conducted to establish the model that relates the backside bead width to the welding current and speed. The dynamic linear model is first constructed and the modeling result is analyzed. The linear model is then improved by incorporating a nonlinear operating point modeled by an ANFIS. Because the weld pool needs to gradually change, being controlled by a skilled welder, a model predictive control is used to follow a trajectory to reach the desired backside bead width and the control increment is penalized. Because the weld pool is not supposed to change in an extremely large range, the resultant model predictive control is actually linear and an analytical solution is derived. Welding experiments confirm that the developed control system is effective in achieving the desired weld joint penetration under various disturbances and initial conditions.

A plasma cloud charge sensor for pulse keyhole process control

Keyhole plasma arc welding achieves much deeper penetration than do all other existing arc welding processes. Because of its ability to penetrate thicker material, the control of the keyhole in plasma arc welding becomes critical. From an analysis of the physical process, a sensor to detect the state of the keyhole for keyhole process control has been proposed and developed. This sensor measures the electrical effect of the plasma cloud generated during keyhole plasma arc welding. It is found that the plasma cloud, which rapidly decreases to zero upon establishment of the fully penetrated keyhole, can be used to detect the state of the keyhole reliably. The effectiveness of the proposed sensor for detecting the keyhole state has been verified during pulse keyhole plasma arc welding.

Real-Time Sensing of Sag Geometry During GTA Welding

Seam tracking and weld penetration control are two fundamental issues in automated welding. Although the seam tracking technique has matured, the latter still remains a unique unsolved problem. It was found that the full penetration status during GTA welding can be determined with sufficient accuracy using the sag depression. To achieve a new full penetration sensing technique, a structured-light 3D vision system is developed to extract the sag geometry behind the pool. The laser stripe, which is the intersection of the structured-light and weldment, is thinned and then used to acquire the sag geometry. To reduce possible control delay, a small distance is selected between the pool rear and laser stripe. An adaptive dynamic search for rapid thinning of the stripe and the maximum principle of slope difference for unbiased recognition of sag border were proposed to develop an effective real-time image processing algorithm for sag geometry acquisition. Experiments have shown that the proposed sensor and image algorithm can provide reliable feedback information of sag geometry for the full penetration control system.

Metal Transfer in Double-Electrode Gas Metal Arc Welding

Gas metal arc welding (GMAW) is the most widely used process for metal joining because of its high productivity and good quality, but analysis shows that the fundamental characteristic restricts conventional GMAW from further increasing the welding productivity. A novel GMAW process, refereed to as double-electrode GMAW or DE-GMAW, thus has been developed to make it possible to increase the melting current while the base metal current can still be controlled at a desired level. This fundamental change provides an effective method to allow manufacturers to use high melting currents to achieve high melting speed and low base metal heat input. A series of experiments have been conducted to uncover the basic characteristics of this novel process. Results obtained from analyses of high-speed image sequences and recorded current signals suggest that DE-GMAW can lower the critical current for achieving the desired spray transfer, shift the droplet trajectory, reduce the diameter of the droplet, and increase the speed and (generation) rate of the droplets.