08 مهر 1401

سید سجاد موسوی فرد

مرتبه علمی: استادیار
نشانی:
تحصیلات: دکترای تخصصی / فیزیک - اتمی مولکولی زمینه اپتیک
تلفن:
دانشکده: معاونت آموزشی و پژوهشی (ویژه گروه علوم پایه)

مشخصات پژوهش

عنوان
Quantitative Analysis and Identification Improvement in Laser-Induced Breakdown Spectroscopy by Self-Absorption Correction and Artificial Neural Network
نوع پژوهش مقاله چاپ شده
کلیدواژه‌ها
Training , Adaptive optics , Neurons , Metals , Logic gates , Plasmas , Optical variables measurement
پژوهشگران امیر حسین فرهادیان (نفر اول)، سید سجاد موسوی فرد (نفر دوم)

چکیده

Abstract: In this research, the laser-induced breakdown spectroscopy (LIBS) technique is used for concentration prediction and identification in aluminum alloys. For this purpose, calibration-free LIBS (CF-LIBS) and artificial neural network (ANN) analyses were implemented. Self-absorption correction (SAC) and gate time improvement in CF-LIBS lead to more accurate quantitative results and concentration calculation close to real values. In addition, in identification of different Al alloys by ANNs, results show that using corrected lines intensity of fundamental species has better results in network construction and fewer errors.