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.
Resistance spot welding is one of the most important welding procedures. Therefore, a strong emphasis is placed on the quality of the welds. One of the phenomena that causes the deterioration in quality is the eruption of molten material, the so-called expulsion. Expulsion can be avoided with appropriate parameter selection. The problem, however, lies in the fact that the best quality welds are made with parameters just below the expulsion area. Therefore, for any successful control scheme an efficient and dependable expulsion detection is needed. A linear vector quantization (LVQ) neural network system is proposed to achieve this goal. The network is analysed with different sensor combinations and different materials. The results show that the LVQ neural network is able to detect the expulsion in different materials. The experiment also points to the welding force signal as the most important indicator of the expulsion occurrence.
The present paper presents the influence of welding current shape on weld strength of resistance spot welds of zinc coated mild steel sheets. The influence is analysed at different levels of the electrode wear. Welding currents with different peak values and different RMS (root mean square) values were used in the experiment. The results show that welding current with high peak values implies higher weld strength.
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.
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