The paper presents the results of experimental gas metal arc welding. Namely, this welding process is commonly used in the automation and robotization of fusion welding, where adaptive regulation is indispensable. In addition to variable welding voltage and current, a distinctive characteristic of arc welding processes are also the pressure of audible sound phenomena which reflect the variable conditions in the arc to the highest extent. It follows that it is reasonable to monitor these phenomena and that the results can be used for the implementation of adaptive welding process control.

A burning of the electric arc produces strong side effects such as UV light, heat, vibrations of the burning electrode, acoustic emission, and audible sound. In addition to variable welding voltage and current, a distinctive characteristic of arc welding processes is the pressures of audible sound phenomena which reflect the variable conditions in the arc to the highest extent. Measurements and analysis of audible sound generated by the GMAW are presented in this paper. Results indicate that more information about the welding process is embedded in the sound signal as in the welding current signal or/and in the welding voltage signal. An additional advantage of sound implementation into the control algorithms is simplicity of its detection. The mathematical model for the calculation of sound from the welding current is presented. The model can be implemented for the calculation of welding process parameters in real–time applications.

The contribution gives an insight into resistance flash welding with emphasis on process dynamics. For the experiments ribbed mild steel concrete reinforcement bars were used with a range of welding parameters used in a normal welding praxis. The welded bars were tested for tensile strength and the results were used to develop a regression model. The model was designed to predict weld piece strength according to input welding parameters. The input welding parameters were: welding force, welding current and welding time.

Abstract: In addition to variable welding voltage and current, a distinctive characteristic of arc welding processes are also the light and audible phenomena, which reflect the variable conditions in the arc to the highest extent. It follows that it is reasonable to monitor these phenomena and that the results can be used for the implementation of adaptive welding process control. The paper presents the results of experimental gas metal arc welding. Namely, this welding process is commonly used in the automation and robotization of fusion welding, where adaptive regulation is indispensable.

A new method for measuring the time-dependent displacement and deformation of electrodes during resistance spot welding (RSW) is described. The method allows assessment of the non-stationary thermal expansion of the electrodes. By measuring the electrode indentation close to the weld-piece surface, the method enables a better estimation of indentation than the present methods that rely on measurement of the displacement of the outside part of the electrodes or their holders. The method is based on using a digital video camera to acquire image sequences of electrode caps in the RSW process. A regular pattern of shallow bores is drilled into the caps to enhance the contrast of the acquired images and facilitate image processing. The distances between the bores are analyzed from the image sequences to determine the temporally and spatially resolved displacement and deformation of the caps. The analysis revealed that the cap deformations in some welding regimes can reach up to 20% of the maximum cap displacements, which are approximately 200 µm. The employed image processing algorithms are presented as well as examples of results that demonstrate the applicability of the method.

The most frequently used arc welding process is gas metal arc welding (GMAW). Different methods are in use for monitoring the quality of a welding process. In this paper sound generated during the GMAW process is used for assessing and monitoring of the welding process and for prediction of welding process stability and quality. Theoretical and experimental analyses of the acoustic signals have shown that there are two main noise-generating mechanisms; the first is arc extinction and arc ignition having impulse character, the second is the arc itself acting as an ionization sound source. A new algorithm based on the measured welding current was established for the calculation of emitted sound during the welding process. The algorithm was verified for different welding condition, different welding materials and different specimen. The comparisons have shown that the calculated values are in good agreement with the measured values of sound signal.

Resistance spot welding is frequently used welding method in a mass production like: electric industry, production of white goods and production of body assembly in automotive industry. Selected welding parameters often cause excessive input, that assure better reliability of full penetrating welds even in the case of deviations of sheet thickness, surface conditions and deviations of electrode tips due to heat and mechanical damage influences. Excessive energy inputs lead to excessive heating of welded material that can cause unwanted expulsions and electrode tips damages. It shows up that in such cases we get unwanted surface appearance of welded pieces at excessive energy consumption with negative environmental influence and more expensive process. This is way users want different sensors systems to monitor and control the welding process to attain optimal conditions. The research was conducted with welding inverter that is as a rule used in robotized RSW particularly in automotive industry. Research results confirm possibility to evaluate RSW process state based on analyses of continuous AE signals during current flow. Continuous signal were analyzed in time and frequency domain.

Acoustic emission provides information on the process of nugget formation in resistance spot welding and on the quality of the weld. The information obtained on the basis of acoustic emission can either confirm or reject the conclusions about weld quality. In the research, the acoustic emission signal was compared to the results of the measured electrical properties including voltage, current, and calculated resistance. The aim of the research was to analyse the possibility of predicting expulsion during resistance spot welding on the basis of the acoustic emission signal a few moments before its appearance, by using a PZT sensor mounted on the lower electrode. The research was performed on a mild steel of good weldability which is frequently used in mass production, particularly in automotive industry.

Acoustic emission provides information on the process of nugget formation in resistance spot welding and on the quality of the weld. The information obtained on the basis of acoustic emission can either confirm or reject the conclusions about weld quality. In the research, the acoustic emission signal was compared to the results of the measured electrical properties including voltage, current, and calculated resistance. The aim of the research was to analyse the possibility of predicting expulsion during resistance spot welding on the basis of the acoustic emission signal a few moments before its appearance, by using a PZT sensor mounted on the lower electrode. The research was performed on a mild steel of good weldability which is frequently used in mass production, particularly in automotive industry.

This paper presents an overview of resistance spot welding control. The presentation of the physical background of the resistance welding process is followed by the description of the main problems concerning the appurtenant control theory. Solutions to these problems are presented primarily according to the measured signals used and to the type of control strategies.

The contribution treats of the development of a system for resistance spot welding of a release, which is a part of a motor protective switch. There are five welds among dissimilar materials on the release. For economical reasons the welds need to be produced using the same source, but with different welding parameters. The contribution presents the release and its function, its weld specifications, the development of the welding system, the determination of the welding parameters for one of the key resistance spot welds and the achieved results.

In this paper sound generated during the gas-metal arc welding process was studded. Experimental analyses of the acoustic signals have shown that there are two main noise-generating mechanisms, first having impulse form is arc extinction and arc ignition; the second is the arc itself acting as an ionization sound source. The sound signal is used for assessing and monitoring of the welding process, and for prediction of welding process stability and quality. A new algorithm based on the measured welding current was established for the calculation of emitted sound during the welding process. The comparisons have shown that the calculated values are in good agreement with the measured values. ~ujni zvuk, koja se generira kod procesa elektrolu~nog zavarivanja po MAG postupku. Eksperimentalna analiza zvu~nog signala je pokazala, da se javljaju dva glavna mehanizma generiranja zvuka, prvi, koji ima karakter impulza, je posljedica paljenja i ga{enja elektri~nog luka (plazme); drugi je sam elektri~ni luk, koji djeluje kao ioniziraju~i izvor zvuka. Zvu~ni signal je upotrijebljen za ocjenjivanje i nadzor procesa zavarivanja, te za ocjenjivanje kvalitete i stabilnosti procesa zavarivanja. Razvijen je novi matemati~ki model za izra~un emitiranog zvuka kod procesa zavarivanja a koji bazira na izmjerenoj struji zavarivanja. Usporedba izra~unanih i izmjerenih vrijednosti zvu~nog signala je pokazala veliku suglasnost.

We have developed a scanning laser system based on the optical triangulation principle for the shape measurement of fusion weld surfaces. The system integrates a triangulation module consisting of a laser line projector and a digital video camera with a mechanical scanning stage and an industrial computer. The system is small and rugged, suitable for application in industrial environment. The system can sample a weld surface at a rate of up to 30 profiles per second achieving 0.1mm accuracy. Software was developed which analyses the captured weld surface shape in real time determining the characteristic shape parameters (length, width, height, cross section, volume, starting position,...) which are then used for automated classification of the welds into acceptable and unacceptable. The software also detects surface defects such as undercutting, holes or melt splash, etc. The system has been tested in a robotized welding cell for automotive parts in an industrial production facility. Weld classification obtained by the system was compared to an independent classification determined by a trained weld inspector on the basis of visual inspection and to another one determined on the basis of metallographic analysis of the weld. Using the metallographic based classification as the reference we find that the developed weld inspection system can achieve better classification reliability than a trained visual weld inspector.

The goal of this study was to estimate the requirements, stresses and noxiousness imposed upon a welder at his work station. Measurements were carried out in MAG welding, a process most often used in industry. The paper presents the results of the measurement analysis (methods of Owas and Corlett, noise-induced hearing loss) at the welder's work station. The results show that the welder's work is very intense, the welder's poise non-physiological, and in some parts of his body certain discomfort or even pain may occur. Based on the results technological, organisational and personal measures are proposed in order to minimize the load and make welder's jab easier.