FEM-Based Thermogram Correction for Inconel 625 Joint Hardness Clustering

Assessing the temperature of the joint in on-line mode is a vital task that is demanded to characterize the formations of terns formations that are taking place in a joint and result in reaching necessary properties of the joint. Arc welding generates a high amount of heat that is reflected by the metallic surface of the welded object. In the paper, a temperature measurement credibility increase method is described and evaluated. The proposed method is used to reduce the influence of the reflected temperature of the hot torch and the arc on the temperature distribution observed on the surface of the welded joint using an infrared camera. The elaborated approach is based on comparison between infrared observation of the solidifying weld and precisely performed finite element method (FEM) simulation. The FEM simulations were calibrated according to the geometry of the fusion zone. It allows to precisely model heat source properties. The best-reflected temperature correction map was selected and applied to obtain a temperature representation that differs from the FEM baseline by less than 10 °C. Precise temperature values allowed us to cluster welded joints in 3D feature space (temperature, hardness, linear energy). It was found that by using the k-means clustering method it is possible to distinguish between correct and faulty (in terms of too low mechanical properties) joints.

Influence of Gravity on Molten Pool Behavior and Analysis of Microstructure on Various Welding Positions in Pulsed Gas Metal Arc Welding

This study performed welding on various welding positions in the flat, overhead, and vertical down positions using a pulsed gas metal arc welding (P-GMAW) process. Despite the same amount of heat input on various welding positions, the welding characteristics varied depending on the welding positions. The effect of gravity on the welding process determined the different formation of the weld bead, and the influence of molten pool behavior on various welding positions changed the microstructure in the weld metal. The current and voltage signals were synchronized with a high-speed camera using a data acquisition (DAQ) system. To induce the one pulse one drop (OPOD) process of metal transfer, the shielding gas was used 95% Ar+5% CO2. The microstructure of the weld metal was analyzed in relation to molten pool behavior.

Sensor Fusion to Estimate the Depth and Width of the Weld Bead in Real Time in GMAW Processes

The arc welding process is widely used in industry but its automatic control is limited by the difficulty in measuring the weld bead geometry and closing the control loop on the arc, which has adverse environmental conditions. To address this problem, this work proposes a system to capture the welding variables and send stimuli to the Gas Metal Arc Welding (GMAW) conventional process with a constant voltage power source, which allows weld bead geometry estimation with an open-loop control. Dynamic models of depth and width estimators of the weld bead are implemented based on the fusion of thermographic data, welding current and welding voltage in a multilayer perceptron neural network. The estimators were trained and validated off-line with data from a novel algorithm developed to extract the features of the infrared image, a laser profilometer was implemented to measure the bead dimensions and an image processing algorithm that measures depth by making a longitudinal cut in the weld bead. These estimators are optimized for embedded devices and real-time processing and were implemented on a Field-Programmable Gate Array (FPGA) device. Experiments to collect data, train and validate the estimators are presented and discussed. The results show that the proposed method is useful in industrial and research environments.

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.

Current Issues and Problems in Welding Science

Losses of life and property due to catastrophic failure of structures are often traced to defective welds. However, major advances have taken place in welding science and technology in the last few decades. With the development of new methodologies at the crossroad of basic and applied sciences, the promise of science-based tailoring of composition, structure, and properties of the weldments may be fulfilled. This will require resolution of several contemporary issues and problems concerning the structure and properties of the weldments as well as intelligent control and automation of the welding processes.