{"title":"PT-Kriging法在木材内部缺陷应力波三维成像中的应用","authors":"Yifei Li, Xiaochen Du, Hailin Feng, Y. Fang","doi":"10.1109/icomssc45026.2018.8941799","DOIUrl":null,"url":null,"abstract":"In order to improve the three-dimensional imaging accuracy of stress wave in wood internal defects detection, a three-dimensional stress wave imaging method of wood internal defects based on PT-Kriging (Particle Swarm Optimization Top-k Kriging) is proposed. Based on the ordinary Kriging interpolation, the algorithm is used to fit the mutation function by Particle Swarm Optimization (PSO) optimization algorithm. At the same time, the Top-k query is introduced to find the k known points in the neighborhood so that the high precision of the fitting and the global optimization of the parameters can be realized. Compared with the Kriging algorithm, the algorithm has higher imaging accuracy and can reflect the characteristics of wood internal defects more accurately.","PeriodicalId":332213,"journal":{"name":"2018 International Computers, Signals and Systems Conference (ICOMSSC)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using PT-Kriging Method for Stress Wave Three Dimensional Imaging of Wood Internal Defects\",\"authors\":\"Yifei Li, Xiaochen Du, Hailin Feng, Y. Fang\",\"doi\":\"10.1109/icomssc45026.2018.8941799\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to improve the three-dimensional imaging accuracy of stress wave in wood internal defects detection, a three-dimensional stress wave imaging method of wood internal defects based on PT-Kriging (Particle Swarm Optimization Top-k Kriging) is proposed. Based on the ordinary Kriging interpolation, the algorithm is used to fit the mutation function by Particle Swarm Optimization (PSO) optimization algorithm. At the same time, the Top-k query is introduced to find the k known points in the neighborhood so that the high precision of the fitting and the global optimization of the parameters can be realized. Compared with the Kriging algorithm, the algorithm has higher imaging accuracy and can reflect the characteristics of wood internal defects more accurately.\",\"PeriodicalId\":332213,\"journal\":{\"name\":\"2018 International Computers, Signals and Systems Conference (ICOMSSC)\",\"volume\":\"102 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Computers, Signals and Systems Conference (ICOMSSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icomssc45026.2018.8941799\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Computers, Signals and Systems Conference (ICOMSSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icomssc45026.2018.8941799","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using PT-Kriging Method for Stress Wave Three Dimensional Imaging of Wood Internal Defects
In order to improve the three-dimensional imaging accuracy of stress wave in wood internal defects detection, a three-dimensional stress wave imaging method of wood internal defects based on PT-Kriging (Particle Swarm Optimization Top-k Kriging) is proposed. Based on the ordinary Kriging interpolation, the algorithm is used to fit the mutation function by Particle Swarm Optimization (PSO) optimization algorithm. At the same time, the Top-k query is introduced to find the k known points in the neighborhood so that the high precision of the fitting and the global optimization of the parameters can be realized. Compared with the Kriging algorithm, the algorithm has higher imaging accuracy and can reflect the characteristics of wood internal defects more accurately.