Remote open-path laser-induced breakdown spectroscopy for the analysis of manganese in steel samples at high temperature

作     者：Minchao CUI Yoshihiro DEGUCHI Zhenzhen WANG Seiya TANAKA Min-Gyu JEON Yuki FUJITA Shengdun ZHAO 崔敏超;出口祥啓;王珍珍;田中诚也;全敏奎;藤田裕贵;赵升吨

作者机构：School of Mechanical Engineering Xi'an Jiaotong University Graduate School of Advanced Technology and Science University of Tokushima State Key Laboratory of Multiphase Flow in Power Engineering Xi'an Jiaotong University Division of Mechanical Engineering Korea Maritime and Ocean University School of Mechanical Engineering Xi’an Jiaotong University 

出 版 物：《Plasma Science and Technology》 (等离子体科学和技术（英文版）)

年 卷 期：2019年第21卷第3期

页      面：52-59页

核心收录：

学科分类：08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0827[工学-核科学与技术] 0702[理学-物理学] 

基　　金：supported by National Natural Science Foundation of China (Nos. 51506171 and 51675415) National Natural Science Foundation of China for Key Program (No. 51335009) National Key Research and Development Program of China (No. 2017YFD0700200) the joint research fund between Tokushima University and Xi’an Jiaotong University 

主　　题：remote open-path LIBS steel manganese sample temperature quantitative analysis 

摘      要：A remote open-path laser-induced breakdown spectroscopy(LIBS) system was designed and studied in the present work for the purpose of combining the LIBS technique with the steel production line. In this system, the relatively simple configuration and optics were employed to measure the steel samples at a remote distance and a hot sample temperature. The system has obtained a robustness for the deviation of the sample position because of the open-path and alloptical structure. The measurement was carried out at different sample temperatures by placing the samples in a muffle furnace with a window in the front door. The results show that the intensity of the spectral lines increased as the sample temperature increased. The influence of the sample temperature on the quantitative analysis of manganese in the steel samples was investigated by measuring ten standard steel samples at different temperatures. Three samples were selected as the test sample for the simulation measurement. The results show that, at the sample temperature of 500 ℃, the average relative error of prediction is 3.1% and the average relative standard deviation is 7.7%, respectively.