Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis

Detalhes bibliográficos
Autor(a) principal: Bevans, Benjamin
Data de Publicação: 2023
Outros Autores: Ramalho, André, Smoqi, Ziyad, Gaikwad, Aniruddha, Santos, Telmo G., Rao, Prahalad, Oliveira, J. P.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/151083
Resumo: UID/00667/2020 (UNIDEMI). J. P. Oliveira acknowledges funding by national funds from FCT - Fundação para a Ciência e a Tecnologia, I.P., in the scope of the projects LA/P/0037/2020 Prahalada Rao acknowledges funding from the Department of Energy (DOE), Office of Science, under Grant number DE-SC0021136, and the National Science Foundation (NSF) [Grant numbers CMMI-1719388, CMMI-1920245, CMMI-1739696, CMMI-1752069, PFI-TT 2044710, ECCS 2020246] for funding his research program. This work espousing the concept of online process monitoring in WAAM was funded through the foregoing DOE Grant (Program Officer: Timothy Fitzsimmons), which partially supported the doctoral graduate work of Mr. Benjamin Bevans at University of Nebraska-Lincoln Benjamin, Aniruddha, and Ziyad Smoqi were further supported by the NSF grants CMMI 1752069 (CAREER) and ECCS 2020246. Detecting flaw formation in metal AM using in-situ sensing and graph theory-based algorithms was a major component of CMMI 1752069 (program office: Kevin Chou). Developing machine learning alogirthms for advanced manufacturing applications was the goal of ECCS 2020246 (Program officer: Donald Wunsch). The XCT work was performed at the Nebraska Nanoscale Facility: National Nanotechnology Coordinated Infrastructure under award no. ECCS: 2025298, and with support from the Nebraska Research Initiative through the Nebraska Center for Materials and Nanoscience and the Nanoengineering Research Core Facility at the University of Nebraska-Lincoln. The acquisition of the XCT scanner at University of Nebraska was funded through CMMI 1920245 (Program officer: Wendy Crone). Publisher Copyright: © 2022 The Authors
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spelling Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysisAcoustic sensorGraph theoryProcess flaw monitoringWavelet filteringWire-based directed energy depositionMaterials Science(all)Mechanics of MaterialsMechanical EngineeringUID/00667/2020 (UNIDEMI). J. P. Oliveira acknowledges funding by national funds from FCT - Fundação para a Ciência e a Tecnologia, I.P., in the scope of the projects LA/P/0037/2020 Prahalada Rao acknowledges funding from the Department of Energy (DOE), Office of Science, under Grant number DE-SC0021136, and the National Science Foundation (NSF) [Grant numbers CMMI-1719388, CMMI-1920245, CMMI-1739696, CMMI-1752069, PFI-TT 2044710, ECCS 2020246] for funding his research program. This work espousing the concept of online process monitoring in WAAM was funded through the foregoing DOE Grant (Program Officer: Timothy Fitzsimmons), which partially supported the doctoral graduate work of Mr. Benjamin Bevans at University of Nebraska-Lincoln Benjamin, Aniruddha, and Ziyad Smoqi were further supported by the NSF grants CMMI 1752069 (CAREER) and ECCS 2020246. Detecting flaw formation in metal AM using in-situ sensing and graph theory-based algorithms was a major component of CMMI 1752069 (program office: Kevin Chou). Developing machine learning alogirthms for advanced manufacturing applications was the goal of ECCS 2020246 (Program officer: Donald Wunsch). The XCT work was performed at the Nebraska Nanoscale Facility: National Nanotechnology Coordinated Infrastructure under award no. ECCS: 2025298, and with support from the Nebraska Research Initiative through the Nebraska Center for Materials and Nanoscience and the Nanoengineering Research Core Facility at the University of Nebraska-Lincoln. The acquisition of the XCT scanner at University of Nebraska was funded through CMMI 1920245 (Program officer: Wendy Crone). Publisher Copyright: © 2022 The AuthorsThe goal of this work is to detect flaw formation in the wire-based directed energy deposition (W-DED) process using in-situ sensor data. The W-DED studied in this work is analogous to metal inert gas electric arc welding. The adoption of W-DED in industry is limited because the process is susceptible to stochastic and environmental disturbances that cause instabilities in the electric arc, eventually leading to flaw formation, such as porosity and suboptimal geometric integrity. Moreover, due to the large size of W-DED parts, it is difficult to detect flaws post-process using non-destructive techniques, such as X-ray computed tomography. Accordingly, the objective of this work is to detect flaw formation in W-DED parts using data acquired from an acoustic (sound) sensor installed near the electric arc. To realize this objective, we develop and apply a novel wavelet integrated graph theory approach. The approach extracts a single feature called graph Laplacian Fiedler number from the noise-contaminated acoustic sensor data, which is subsequently tracked in a statistical control chart. Using this approach, the onset of various types of flaws are detected with a false alarm rate less-than 2%. This work demonstrates the potential of using advanced data analytics for in-situ monitoring of W-DED.DEMI - Departamento de Engenharia Mecânica e IndustrialUNIDEMI - Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e IndustrialCENIMAT-i3N - Centro de Investigação de Materiais (Lab. Associado I3N)DCM - Departamento de Ciência dos MateriaisRUNBevans, BenjaminRamalho, AndréSmoqi, ZiyadGaikwad, AniruddhaSantos, Telmo G.Rao, PrahaladOliveira, J. P.2023-03-22T22:29:18Z2023-012023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article16application/pdfhttp://hdl.handle.net/10362/151083engBevans, B., Ramalho, A., Smoqi, Z., Gaikwad, A., Santos, T. G., Rao, P., & Oliveira, J. P. (2023). Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis. Materials and Design, 225, [111480]. https://doi.org/10.1016/j.matdes.2022.1114800264-1275PURE: 56630103https://doi.org/10.1016/j.matdes.2022.111480info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:33:32Zoai:run.unl.pt:10362/151083Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:54:27.336053Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis
title Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis
spellingShingle Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis
Bevans, Benjamin
Acoustic sensor
Graph theory
Process flaw monitoring
Wavelet filtering
Wire-based directed energy deposition
Materials Science(all)
Mechanics of Materials
Mechanical Engineering
title_short Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis
title_full Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis
title_fullStr Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis
title_full_unstemmed Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis
title_sort Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis
author Bevans, Benjamin
author_facet Bevans, Benjamin
Ramalho, André
Smoqi, Ziyad
Gaikwad, Aniruddha
Santos, Telmo G.
Rao, Prahalad
Oliveira, J. P.
author_role author
author2 Ramalho, André
Smoqi, Ziyad
Gaikwad, Aniruddha
Santos, Telmo G.
Rao, Prahalad
Oliveira, J. P.
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv DEMI - Departamento de Engenharia Mecânica e Industrial
UNIDEMI - Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e Industrial
CENIMAT-i3N - Centro de Investigação de Materiais (Lab. Associado I3N)
DCM - Departamento de Ciência dos Materiais
RUN
dc.contributor.author.fl_str_mv Bevans, Benjamin
Ramalho, André
Smoqi, Ziyad
Gaikwad, Aniruddha
Santos, Telmo G.
Rao, Prahalad
Oliveira, J. P.
dc.subject.por.fl_str_mv Acoustic sensor
Graph theory
Process flaw monitoring
Wavelet filtering
Wire-based directed energy deposition
Materials Science(all)
Mechanics of Materials
Mechanical Engineering
topic Acoustic sensor
Graph theory
Process flaw monitoring
Wavelet filtering
Wire-based directed energy deposition
Materials Science(all)
Mechanics of Materials
Mechanical Engineering
description UID/00667/2020 (UNIDEMI). J. P. Oliveira acknowledges funding by national funds from FCT - Fundação para a Ciência e a Tecnologia, I.P., in the scope of the projects LA/P/0037/2020 Prahalada Rao acknowledges funding from the Department of Energy (DOE), Office of Science, under Grant number DE-SC0021136, and the National Science Foundation (NSF) [Grant numbers CMMI-1719388, CMMI-1920245, CMMI-1739696, CMMI-1752069, PFI-TT 2044710, ECCS 2020246] for funding his research program. This work espousing the concept of online process monitoring in WAAM was funded through the foregoing DOE Grant (Program Officer: Timothy Fitzsimmons), which partially supported the doctoral graduate work of Mr. Benjamin Bevans at University of Nebraska-Lincoln Benjamin, Aniruddha, and Ziyad Smoqi were further supported by the NSF grants CMMI 1752069 (CAREER) and ECCS 2020246. Detecting flaw formation in metal AM using in-situ sensing and graph theory-based algorithms was a major component of CMMI 1752069 (program office: Kevin Chou). Developing machine learning alogirthms for advanced manufacturing applications was the goal of ECCS 2020246 (Program officer: Donald Wunsch). The XCT work was performed at the Nebraska Nanoscale Facility: National Nanotechnology Coordinated Infrastructure under award no. ECCS: 2025298, and with support from the Nebraska Research Initiative through the Nebraska Center for Materials and Nanoscience and the Nanoengineering Research Core Facility at the University of Nebraska-Lincoln. The acquisition of the XCT scanner at University of Nebraska was funded through CMMI 1920245 (Program officer: Wendy Crone). Publisher Copyright: © 2022 The Authors
publishDate 2023
dc.date.none.fl_str_mv 2023-03-22T22:29:18Z
2023-01
2023-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/151083
url http://hdl.handle.net/10362/151083
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Bevans, B., Ramalho, A., Smoqi, Z., Gaikwad, A., Santos, T. G., Rao, P., & Oliveira, J. P. (2023). Monitoring and flaw detection during wire-based directed energy deposition using in-situ acoustic sensing and wavelet graph signal analysis. Materials and Design, 225, [111480]. https://doi.org/10.1016/j.matdes.2022.111480
0264-1275
PURE: 56630103
https://doi.org/10.1016/j.matdes.2022.111480
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