Songqi Zhang, S. Enk, Moritz Kolter, J. Schleifenbaum
{"title":"Polarized Illumination for Optical Monitoring System in Laser Powder Bed Fusion","authors":"Songqi Zhang, S. Enk, Moritz Kolter, J. Schleifenbaum","doi":"10.1115/iam2022-94437","DOIUrl":null,"url":null,"abstract":"\n Laser powder bed fusion (LPBF) is a promising technology to manufacture complex geometry in a layer wised manner. Shifting from low volume prototyping to high volume production the demand for quality assurance and reliability of additive manufacturing systems increases hence in-situ monitoring systems are required to monitor process anomalies as input for further process control. Optical based monitoring systems, such as CMOS and CCD camera, are proved as an effective way to monitor layer wise geometrical distortion during manufacturing process. However, due to complex illumination condition in the process chamber, geometries of the printed parts are hard to distinguished and extracted from powder bed properly. In this study, we propose a novel method for an illumination setup by using polarized light sources to improve the distinguishability of printed parts compared to the powder bed on the layer wised monitoring images. In the proposed setup LED light sources are installed on each side of the optical camera with polarizing filters. For every printed layer, two images of powder bed are captured using each light source before recoating. The images are calibrated and stacked afterwards to get the polarized monitoring image at the current layer. The polarized image made in the new setup shows significant improvement of contrast between printed part and powder. The illumination setup was tested on an EOS M290 LPBF machine with AlSi10Mg powder. Polarized monitoring images were compared with images under original machine illumination. The result shows the distinguishable difference between grey values of printed parts and powder bed, where the geometry of the printed part can be extracted with F1 score = 0.977 using Otsu binarization algorithm.","PeriodicalId":184278,"journal":{"name":"2022 International Additive Manufacturing Conference","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Additive Manufacturing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/iam2022-94437","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
Laser powder bed fusion (LPBF) is a promising technology to manufacture complex geometry in a layer wised manner. Shifting from low volume prototyping to high volume production the demand for quality assurance and reliability of additive manufacturing systems increases hence in-situ monitoring systems are required to monitor process anomalies as input for further process control. Optical based monitoring systems, such as CMOS and CCD camera, are proved as an effective way to monitor layer wise geometrical distortion during manufacturing process. However, due to complex illumination condition in the process chamber, geometries of the printed parts are hard to distinguished and extracted from powder bed properly. In this study, we propose a novel method for an illumination setup by using polarized light sources to improve the distinguishability of printed parts compared to the powder bed on the layer wised monitoring images. In the proposed setup LED light sources are installed on each side of the optical camera with polarizing filters. For every printed layer, two images of powder bed are captured using each light source before recoating. The images are calibrated and stacked afterwards to get the polarized monitoring image at the current layer. The polarized image made in the new setup shows significant improvement of contrast between printed part and powder. The illumination setup was tested on an EOS M290 LPBF machine with AlSi10Mg powder. Polarized monitoring images were compared with images under original machine illumination. The result shows the distinguishable difference between grey values of printed parts and powder bed, where the geometry of the printed part can be extracted with F1 score = 0.977 using Otsu binarization algorithm.