文献类型：期刊文献

英文题名：Nondestructive Evaluation of Thermal Barrier Coatings Thickness Using Terahertz Technique Combined with PCA-GA-ELM Algorithm

作者：Yuan, Baohan[1];Wang, Weize[1];Ye, Dongdong[1,2];Zhang, Zhenghao[3];Fang, Huanjie[1];Yang, Ting[1];Wang, Yihao[1];Zhong, Shuncong[3]

机构：[1]East China Univ Sci & Technol, Sch Mech & Power Engn, Key Lab Pressure Syst & Safety, Minist Educ, 130 Meilong Rd, Shanghai 200237, Peoples R China;[2]Anhui Polytech Univ, Sch Artificial Intelligence, Wuhu 241000, Peoples R China;[3]Fuzhou Univ, Sch Mech Engn & Automat, Lab Opt Terahertz & Nondestruct Testing, Fuzhou 350108, Peoples R China

年份：2022

卷号：12

期号：3

外文期刊名：COATINGS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000775612700001)】；

基金：This research was funded by the National Natural Science Foundation of China (Grant No. 52175136), Science Center for Gas Turbine Project (P2021-A-IV-002-002), and Shanghai Joint Innovation Program in the Field of Commercial Aviation Engines.

语种：英文

外文关键词：TBCs; terahertz time-domain spectroscopy; thickness; PCA-GA-ELM

摘要：Thermal barrier coatings (TBCs) are usually used in high temperature and harsh environment, resulting in thinning or even spalling off. Hence, it is vital to detect the thickness of the TBCs. In this study, a hybrid machine learning model combined with terahertz time-domain spectroscopy technology was designed to predict the thickness of TBCs. The terahertz signals were obtained from the samples prepared in laboratory and actual turbine blade. The principal component analysis (PCA) method was used to decrease the data dimensions. Finally, an extreme learning machine (ELM) was proposed to establish the thickness of TBCs prediction model. Genetic algorithm (GA) was selected to optimize the model to make it more accurate. The results showed that the root correlation coefficient (R-2) exceeded 0.97 and the errors (root mean square error and mean absolute percentage error) were less than 2.57. This study proposes that terahertz time-domain technology combined with PCA-GA-ELM model is accurate and feasible for evaluating the thickness of the TBCs.