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In this study, the ultrasonic technique and the artificial neural network optimized with the genetic algorithm (GA_BPNN) are combined to develop an intelligent method for automatic detection and accurate prediction of TBCs\u2019s porosity. A series of physical models of plasma\u2010sprayed ZrO<jats:sub>2<\/jats:sub> coating are established with a thickness of 288\u2009<jats:italic>\u03bc<\/jats:italic>m and porosity varying from 5.71% to 26.59%, and the ultrasonic reflection coefficient amplitude spectrum (URCAS) is constructed based on the time\u2010domain numerical simulation signal. The characteristic features (<jats:italic>f<\/jats:italic><jats:sub>1<\/jats:sub>, <jats:italic>f<\/jats:italic><jats:sub>2<\/jats:sub>, <jats:italic>A<\/jats:italic><jats:sub>max<\/jats:sub>, \u0394<jats:italic>A<\/jats:italic>) of the URCAS, which are highly dependent on porosity, are extracted as input data to train the GA_BPNN model for predicting the unknown porosity. The average error of the prediction results is 1.45%, which suggests that the proposed method can achieve accurate detection and quantitative characterization of the porosity of TBCs with complex pore morphology.<\/jats:p>","DOI":"10.1155\/2021\/8869928","type":"journal-article","created":{"date-parts":[[2021,4,29]],"date-time":"2021-04-29T18:50:08Z","timestamp":1619722208000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Porosity Characterization of Thermal Barrier Coatings by Ultrasound with Genetic Algorithm Backpropagation Neural Network"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2539-4689","authenticated-orcid":false,"given":"Shuxiao","family":"Zhang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6478-1331","authenticated-orcid":false,"given":"Gaolong","family":"Lv","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9638-4309","authenticated-orcid":false,"given":"Shifeng","family":"Guo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1244-5723","authenticated-orcid":false,"given":"Yanhui","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9845-999X","authenticated-orcid":false,"given":"Wei","family":"Feng","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,4,29]]},"reference":[{"key":"e_1_2_10_1_2","unstructured":"FahrA. 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