Zhuo Yang, B. Lane, Yan Lu, H. Yeung, Jaehyuk Kim, Yande Ndiaye, S. Krishnamurty
{"title":"Using Coaxial Melt Pool Monitoring Images to Estimate Cooling Rate for Powder Bed Fusion Additive Manufacturing","authors":"Zhuo Yang, B. Lane, Yan Lu, H. Yeung, Jaehyuk Kim, Yande Ndiaye, S. Krishnamurty","doi":"10.1115/detc2022-89934","DOIUrl":null,"url":null,"abstract":"\n Cooling rate is a decisive index to characterize melt pool solidification and determine local microstructure formation in metal powder bed fusion processes. Traditional methods to estimate the cooling rate include in-situ temperature measurement and thermal simulation. However, these methods may not be accurate or efficient enough under complex conditions in real-time. This paper proposes a method to approximate the melt pool cooling rate using temperature profile acquired via thermally-calibrated melt pool camera, and based on continuous pixel tracking result. The proposed method can estimate the temperature and associated cooling rate for every pixel immediately, which is potentially applicable for real-time process monitoring. This paper focuses on investigating image data processing, method development, and cooling condition analysis. This work presents the preliminary result of the cooling rate estimation under different conditions such as position, layer number, and overhanging.","PeriodicalId":382970,"journal":{"name":"Volume 2: 42nd Computers and Information in Engineering Conference (CIE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 2: 42nd Computers and Information in Engineering Conference (CIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/detc2022-89934","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
Cooling rate is a decisive index to characterize melt pool solidification and determine local microstructure formation in metal powder bed fusion processes. Traditional methods to estimate the cooling rate include in-situ temperature measurement and thermal simulation. However, these methods may not be accurate or efficient enough under complex conditions in real-time. This paper proposes a method to approximate the melt pool cooling rate using temperature profile acquired via thermally-calibrated melt pool camera, and based on continuous pixel tracking result. The proposed method can estimate the temperature and associated cooling rate for every pixel immediately, which is potentially applicable for real-time process monitoring. This paper focuses on investigating image data processing, method development, and cooling condition analysis. This work presents the preliminary result of the cooling rate estimation under different conditions such as position, layer number, and overhanging.