Yijun Yao, Shaowu Liu, M. Planche, S. Deng, H. Liao
{"title":"Method for Identifying In-Flight Particles based on Digital Image Technologies in Thermal Spraying","authors":"Yijun Yao, Shaowu Liu, M. Planche, S. Deng, H. Liao","doi":"10.31399/ASM.CP.ITSC2021P0664","DOIUrl":null,"url":null,"abstract":"\n In thermal spray processes, the characteristics of in-flight particles (velocity and temperature) have a significant effect on coating performance. Although many imaging systems and algorithms have been developed for identifying and tracking in-flight particles, most are limited in terms of accuracy. One key to solving the tracking problem is to get an algorithm that can distinguish different particles in each image frame. As the study showed, when noise and interference are treated, particles are more readily identified in the background, leading to more accurate size and position measurements with respect to time. This approach is demonstrated and the results discussed.","PeriodicalId":70745,"journal":{"name":"热喷涂技术","volume":"18 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"热喷涂技术","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.31399/ASM.CP.ITSC2021P0664","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In thermal spray processes, the characteristics of in-flight particles (velocity and temperature) have a significant effect on coating performance. Although many imaging systems and algorithms have been developed for identifying and tracking in-flight particles, most are limited in terms of accuracy. One key to solving the tracking problem is to get an algorithm that can distinguish different particles in each image frame. As the study showed, when noise and interference are treated, particles are more readily identified in the background, leading to more accurate size and position measurements with respect to time. This approach is demonstrated and the results discussed.