Application of wavelets for online laser process observer

The online system, plasmo process observer, enables observation of plasma created by e.g. laser welding in two frequency bands, visible and near infrared. The system offers the feature of online detection of failures like pores and enables the user to store the measured data in databases. This paper deals with both aspects. First the application of wavelets for data preprocessing as a first step of online classification of failures is introduced. This time scale-analysis is compared to standard algorithms in frequency or time domain like DFT or digital filters respectively. The second part of this paper shows the capabilities of wavelets for data compression. This is necessary due to the large amount of data generated by the system. It is shown how important data can be extracted of noisy signals by using wavelets. The process observer has been successfully implemented in welding and drilling applications for automotive and aerospace industry with a very high recognition rate of all defects.