Laser-induced damage degree assessment for filters based on static Bayesian network
Menglian Zhou, Jianmin Zhang, Deyan Cheng, Xinwei Lin, Chenghua Wei · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
Two methods were described to quantitatively evaluate the damage of optical filters, which were through detecting the change of transmission coefficient and damaged area of optical filters. Based on the quantitative evaluation results, the laser-induced damage of optical filters was classified five damage degrees, which were undamaged, color changed, slight melt, middle melt and serious melt. The laser-induced damage was uncertain event because there were many uncertain factors to affect the laser-induced damage degree of optical filters. In view of the advantage of the Bayesian network in processing indefinite information, this paper emphatically studied the laser-induced damage degree assessment method of optical filters based on Static Bayesian network. A Bayesian model was constructed to assess the damage degree of filters. Upon our laser-induced damage experiments on the optical filters, the results of the quantitative evaluation were compared with the assessment results of Bayesian network model, which indicated that Bayesian network method was available to assess the laser-induced damage degree of optical filters.