Prediction for incremental damage on final optics in ICF high power laser facility

High power laser facility requires prediction for incremental damage on final optics in order to find varying damage developing trends, then in terms of the trends we can appropriately formulate maintain plans for long-term physical experiment operation on the facility. This essay indicates an image process technology via deep learning. By comparing fit offline optics image with online optics image, the authenticity and the area of the damage can be correctly defined. Besides, due to the comparison we can establish a damage detection model. Through appropriate algorithm and image matching technology, we could manage element damages on the timeline. And the damage varying trends could be found when additionally combined experimental parameter with analysis on specific damage area. Thus the surplus value of assembly can be optimized. By programming a software for elements management this technology could be used on high power laser facility.