Finslerian future-past asymmetry

Diverse in-process monitoring techniques based on acoustic, chromatic and intelligent approaches have been developed for laser cleaning not only to achieve the sound-cleaned surface but also to control the process in an automatic manner. The cleaning of various materials such as copper, marble, paper have also been carried out by using Q-switched Nd:YAG radiation. The process was successfully monitored by detecting the acoustic emission induced by laser-surface interactions during laser cleaning. Novel surface monitoring was achieved by chromatic modulation technique. The monitoring of laser fluence based on neural network logic was carried out by means of the recognition of acoustic spectrum patterns. The prediction system of surface damage has been also developed using fuzzy rule base in the same way as a human expert. These techniques may provide unique information for characterising the process as well as a promise of successful applications for laser cleaning techniques in real practical fields.