The here presented monitoring method is based on the UV-light detection being emitted by the welding plasma plume and the measurement of the near-IR radiation of the glowing spatters which are thrown out of the welding pool. The results of the above mentioned spatter detection are used to approximate the size of the occurred holes in the weld. A third sensor is used for monitoring the workpiece temperature. This additional signal is very important when welding thin metal sheets (e.g. overlap welds). Further the implementation of the presented monitoring method in an industrial instrument is described. This instrument is a self-learning real-time monitoring system which needs several teach welds for creating a position-true reference. In the following automatic mode it compares the most important features of the actual weld with those of the learned reference. Using fuzzy-logic routines the probability is determined that a metallographically important welding failure has happened. The LWM 900 has been developed initially for monitoring the CO2-welding process. The Nd-YAG laser welding process differs slightly from it. This fact has to be considered accordingly for a proper signal detection. Additionally, due to the fact that most of the used detectors are sensitive to the wavelength of the Nd-YAG laser, some measures have to be considered to reject unwanted influences in this connection.
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