Machine Learning-Based Corrosion-Like Defect Estimation With Shear-Horizontal Guided Waves Improved by Mode Separation Article Swipe
Mateus Gheorghe de Castro Ribeiro
,
Alan C. Kubrusly
,
Helon Vicente Hultmann Ayala
,
Steve Dixon
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/access.2021.3063736
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/access.2021.3063736
Shear Horizontal (SH) guided waves have been extensively used to estimate and detect defects in structures like plates and pipes. Depending on the frequency and plate thickness, more than one guided-wave mode propagates, which renders signal interpretation complicated due to mode mixing and complex behavior of each individual mode interacting with defects. This paper investigates the use of machine learning models to analyse the two lowest order SH guided modes, for quantitative size estimation and detection of corrosion-like defects in aluminium plates. The main contribution of the present work is to show that mode separation through machine learning improves the effectiveness of predictive models. Numerical simulations have been performed to generate time series for creating the estimators, while experimental data have been used to validate them. We show that a full mode separation scheme decreased the error rate of the final model by 30% and 67% in defect size estimation and detection respectively.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2021.3063736
- https://ieeexplore.ieee.org/ielx7/6287639/9312710/09369296.pdf
- OA Status
- gold
- Cited By
- 18
- References
- 70
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3135314582
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3135314582Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/access.2021.3063736Digital Object Identifier
- Title
-
Machine Learning-Based Corrosion-Like Defect Estimation With Shear-Horizontal Guided Waves Improved by Mode SeparationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-01-01Full publication date if available
- Authors
-
Mateus Gheorghe de Castro Ribeiro, Alan C. Kubrusly, Helon Vicente Hultmann Ayala, Steve DixonList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2021.3063736Publisher landing page
- PDF URL
-
https://ieeexplore.ieee.org/ielx7/6287639/9312710/09369296.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://ieeexplore.ieee.org/ielx7/6287639/9312710/09369296.pdfDirect OA link when available
- Concepts
-
Estimator, Mode (computer interface), SIGNAL (programming language), Computer science, Guided wave testing, Materials science, Shear (geology), Series (stratigraphy), Algorithm, Acoustics, Physics, Mathematics, Composite material, Geology, Statistics, Operating system, Paleontology, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
18Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 3, 2024: 5, 2023: 4, 2022: 4, 2021: 2Per-year citation counts (last 5 years)
- References (count)
-
70Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3135314582 |
|---|---|
| doi | https://doi.org/10.1109/access.2021.3063736 |
| ids.doi | https://doi.org/10.1109/access.2021.3063736 |
| ids.mag | 3135314582 |
| ids.openalex | https://openalex.org/W3135314582 |
| fwci | 2.23153877 |
| type | article |
| title | Machine Learning-Based Corrosion-Like Defect Estimation With Shear-Horizontal Guided Waves Improved by Mode Separation |
| awards[0].id | https://openalex.org/G5859020988 |
| awards[0].funder_id | https://openalex.org/F4320321091 |
| awards[0].display_name | |
| awards[0].funder_award_id | 001 |
| awards[0].funder_display_name | Coordenação de Aperfeiçoamento de Pessoal de Nível Superior |
| biblio.issue | |
| biblio.volume | 9 |
| biblio.last_page | 40849 |
| biblio.first_page | 40836 |
| grants[0].funder | https://openalex.org/F4320321091 |
| grants[0].award_id | 001 |
| grants[0].funder_display_name | Coordenação de Aperfeiçoamento de Pessoal de Nível Superior |
| topics[0].id | https://openalex.org/T10662 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9998000264167786 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2211 |
| topics[0].subfield.display_name | Mechanics of Materials |
| topics[0].display_name | Ultrasonics and Acoustic Wave Propagation |
| topics[1].id | https://openalex.org/T10534 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9986000061035156 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2205 |
| topics[1].subfield.display_name | Civil and Structural Engineering |
| topics[1].display_name | Structural Health Monitoring Techniques |
| topics[2].id | https://openalex.org/T10205 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.995199978351593 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2208 |
| topics[2].subfield.display_name | Electrical and Electronic Engineering |
| topics[2].display_name | Advanced Fiber Optic Sensors |
| funders[0].id | https://openalex.org/F4320321091 |
| funders[0].ror | https://ror.org/00x0ma614 |
| funders[0].display_name | Coordenação de Aperfeiçoamento de Pessoal de Nível Superior |
| is_xpac | False |
| apc_list.value | 1850 |
| apc_list.currency | USD |
| apc_list.value_usd | 1850 |
| apc_paid.value | 1850 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 1850 |
| concepts[0].id | https://openalex.org/C185429906 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6497624516487122 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1130160 |
| concepts[0].display_name | Estimator |
| concepts[1].id | https://openalex.org/C48677424 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5767261385917664 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q6888088 |
| concepts[1].display_name | Mode (computer interface) |
| concepts[2].id | https://openalex.org/C2779843651 |
| concepts[2].level | 2 |
| concepts[2].score | 0.48357242345809937 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q7390335 |
| concepts[2].display_name | SIGNAL (programming language) |
| concepts[3].id | https://openalex.org/C41008148 |
| concepts[3].level | 0 |
| concepts[3].score | 0.4498525857925415 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[3].display_name | Computer science |
| concepts[4].id | https://openalex.org/C74046356 |
| concepts[4].level | 2 |
| concepts[4].score | 0.4445450007915497 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q5615502 |
| concepts[4].display_name | Guided wave testing |
| concepts[5].id | https://openalex.org/C192562407 |
| concepts[5].level | 0 |
| concepts[5].score | 0.4373604357242584 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q228736 |
| concepts[5].display_name | Materials science |
| concepts[6].id | https://openalex.org/C96035792 |
| concepts[6].level | 2 |
| concepts[6].score | 0.43712812662124634 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q43606218 |
| concepts[6].display_name | Shear (geology) |
| concepts[7].id | https://openalex.org/C143724316 |
| concepts[7].level | 2 |
| concepts[7].score | 0.4216920733451843 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q312468 |
| concepts[7].display_name | Series (stratigraphy) |
| concepts[8].id | https://openalex.org/C11413529 |
| concepts[8].level | 1 |
| concepts[8].score | 0.4171258807182312 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[8].display_name | Algorithm |
| concepts[9].id | https://openalex.org/C24890656 |
| concepts[9].level | 1 |
| concepts[9].score | 0.4041895568370819 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q82811 |
| concepts[9].display_name | Acoustics |
| concepts[10].id | https://openalex.org/C121332964 |
| concepts[10].level | 0 |
| concepts[10].score | 0.1658603847026825 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[10].display_name | Physics |
| concepts[11].id | https://openalex.org/C33923547 |
| concepts[11].level | 0 |
| concepts[11].score | 0.1584218442440033 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[11].display_name | Mathematics |
| concepts[12].id | https://openalex.org/C159985019 |
| concepts[12].level | 1 |
| concepts[12].score | 0.13553792238235474 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q181790 |
| concepts[12].display_name | Composite material |
| concepts[13].id | https://openalex.org/C127313418 |
| concepts[13].level | 0 |
| concepts[13].score | 0.10519647598266602 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q1069 |
| concepts[13].display_name | Geology |
| concepts[14].id | https://openalex.org/C105795698 |
| concepts[14].level | 1 |
| concepts[14].score | 0.08843082189559937 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[14].display_name | Statistics |
| concepts[15].id | https://openalex.org/C111919701 |
| concepts[15].level | 1 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q9135 |
| concepts[15].display_name | Operating system |
| concepts[16].id | https://openalex.org/C151730666 |
| concepts[16].level | 1 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q7205 |
| concepts[16].display_name | Paleontology |
| concepts[17].id | https://openalex.org/C199360897 |
| concepts[17].level | 1 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[17].display_name | Programming language |
| keywords[0].id | https://openalex.org/keywords/estimator |
| keywords[0].score | 0.6497624516487122 |
| keywords[0].display_name | Estimator |
| keywords[1].id | https://openalex.org/keywords/mode |
| keywords[1].score | 0.5767261385917664 |
| keywords[1].display_name | Mode (computer interface) |
| keywords[2].id | https://openalex.org/keywords/signal |
| keywords[2].score | 0.48357242345809937 |
| keywords[2].display_name | SIGNAL (programming language) |
| keywords[3].id | https://openalex.org/keywords/computer-science |
| keywords[3].score | 0.4498525857925415 |
| keywords[3].display_name | Computer science |
| keywords[4].id | https://openalex.org/keywords/guided-wave-testing |
| keywords[4].score | 0.4445450007915497 |
| keywords[4].display_name | Guided wave testing |
| keywords[5].id | https://openalex.org/keywords/materials-science |
| keywords[5].score | 0.4373604357242584 |
| keywords[5].display_name | Materials science |
| keywords[6].id | https://openalex.org/keywords/shear |
| keywords[6].score | 0.43712812662124634 |
| keywords[6].display_name | Shear (geology) |
| keywords[7].id | https://openalex.org/keywords/series |
| keywords[7].score | 0.4216920733451843 |
| keywords[7].display_name | Series (stratigraphy) |
| keywords[8].id | https://openalex.org/keywords/algorithm |
| keywords[8].score | 0.4171258807182312 |
| keywords[8].display_name | Algorithm |
| keywords[9].id | https://openalex.org/keywords/acoustics |
| keywords[9].score | 0.4041895568370819 |
| keywords[9].display_name | Acoustics |
| keywords[10].id | https://openalex.org/keywords/physics |
| keywords[10].score | 0.1658603847026825 |
| keywords[10].display_name | Physics |
| keywords[11].id | https://openalex.org/keywords/mathematics |
| keywords[11].score | 0.1584218442440033 |
| keywords[11].display_name | Mathematics |
| keywords[12].id | https://openalex.org/keywords/composite-material |
| keywords[12].score | 0.13553792238235474 |
| keywords[12].display_name | Composite material |
| keywords[13].id | https://openalex.org/keywords/geology |
| keywords[13].score | 0.10519647598266602 |
| keywords[13].display_name | Geology |
| keywords[14].id | https://openalex.org/keywords/statistics |
| keywords[14].score | 0.08843082189559937 |
| keywords[14].display_name | Statistics |
| language | en |
| locations[0].id | doi:10.1109/access.2021.3063736 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2485537415 |
| locations[0].source.issn | 2169-3536 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2169-3536 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | IEEE Access |
| locations[0].source.host_organization | https://openalex.org/P4310319808 |
| locations[0].source.host_organization_name | Institute of Electrical and Electronics Engineers |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310319808 |
| locations[0].source.host_organization_lineage_names | Institute of Electrical and Electronics Engineers |
| locations[0].license | |
| locations[0].pdf_url | https://ieeexplore.ieee.org/ielx7/6287639/9312710/09369296.pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | IEEE Access |
| locations[0].landing_page_url | https://doi.org/10.1109/access.2021.3063736 |
| locations[1].id | pmh:oai:wrap.warwick.ac.uk:153124 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306400665 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | Warwick Research Archive Portal (University of Warwick) |
| locations[1].source.host_organization | https://openalex.org/I39555362 |
| locations[1].source.host_organization_name | University of Warwick |
| locations[1].source.host_organization_lineage | https://openalex.org/I39555362 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | acceptedVersion |
| locations[1].raw_type | Journal Article |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | False |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | |
| locations[2].id | pmh:oai:doaj.org/article:34871f373ced4e8db9680ec770a32c8a |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S4306401280 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | cc-by-sa |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | https://openalex.org/licenses/cc-by-sa |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | IEEE Access, Vol 9, Pp 40836-40849 (2021) |
| locations[2].landing_page_url | https://doaj.org/article/34871f373ced4e8db9680ec770a32c8a |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5034619730 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-9600-5759 |
| authorships[0].author.display_name | Mateus Gheorghe de Castro Ribeiro |
| authorships[0].countries | BR |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I2699952 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Mechanical Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil |
| authorships[0].institutions[0].id | https://openalex.org/I2699952 |
| authorships[0].institutions[0].ror | https://ror.org/01dg47b60 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I2699952 |
| authorships[0].institutions[0].country_code | BR |
| authorships[0].institutions[0].display_name | Pontifícia Universidade Católica do Rio de Janeiro |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Mateus Gheorghe de Castro Ribeiro |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Mechanical Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil |
| authorships[1].author.id | https://openalex.org/A5039024914 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-8633-4903 |
| authorships[1].author.display_name | Alan C. Kubrusly |
| authorships[1].countries | BR |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I2699952 |
| authorships[1].affiliations[0].raw_affiliation_string | Centre for Telecommunication Studies, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil |
| authorships[1].institutions[0].id | https://openalex.org/I2699952 |
| authorships[1].institutions[0].ror | https://ror.org/01dg47b60 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I2699952 |
| authorships[1].institutions[0].country_code | BR |
| authorships[1].institutions[0].display_name | Pontifícia Universidade Católica do Rio de Janeiro |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Alan Conci Kubrusly |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Centre for Telecommunication Studies, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil |
| authorships[2].author.id | https://openalex.org/A5032061545 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-5406-3902 |
| authorships[2].author.display_name | Helon Vicente Hultmann Ayala |
| authorships[2].countries | BR |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I2699952 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Mechanical Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil |
| authorships[2].institutions[0].id | https://openalex.org/I2699952 |
| authorships[2].institutions[0].ror | https://ror.org/01dg47b60 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I2699952 |
| authorships[2].institutions[0].country_code | BR |
| authorships[2].institutions[0].display_name | Pontifícia Universidade Católica do Rio de Janeiro |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Helon Vicente Hultmann Ayala |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Mechanical Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro, Brazil |
| authorships[3].author.id | https://openalex.org/A5078123747 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-7536-961X |
| authorships[3].author.display_name | Steve Dixon |
| authorships[3].countries | GB |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I39555362 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Physics, University of Warwick, Coventry, U.K. |
| authorships[3].institutions[0].id | https://openalex.org/I39555362 |
| authorships[3].institutions[0].ror | https://ror.org/01a77tt86 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I39555362 |
| authorships[3].institutions[0].country_code | GB |
| authorships[3].institutions[0].display_name | University of Warwick |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | Steve Dixon |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Department of Physics, University of Warwick, Coventry, U.K. |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://ieeexplore.ieee.org/ielx7/6287639/9312710/09369296.pdf |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Machine Learning-Based Corrosion-Like Defect Estimation With Shear-Horizontal Guided Waves Improved by Mode Separation |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10662 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9998000264167786 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2211 |
| primary_topic.subfield.display_name | Mechanics of Materials |
| primary_topic.display_name | Ultrasonics and Acoustic Wave Propagation |
| related_works | https://openalex.org/W4287880334, https://openalex.org/W4366700029, https://openalex.org/W4285230481, https://openalex.org/W4385769873, https://openalex.org/W4281634296, https://openalex.org/W4319161863, https://openalex.org/W2371687270, https://openalex.org/W4311888330, https://openalex.org/W4248537703, https://openalex.org/W2745131833 |
| cited_by_count | 18 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 3 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 5 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 4 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 4 |
| counts_by_year[4].year | 2021 |
| counts_by_year[4].cited_by_count | 2 |
| locations_count | 3 |
| best_oa_location.id | doi:10.1109/access.2021.3063736 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2485537415 |
| best_oa_location.source.issn | 2169-3536 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2169-3536 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | IEEE Access |
| best_oa_location.source.host_organization | https://openalex.org/P4310319808 |
| best_oa_location.source.host_organization_name | Institute of Electrical and Electronics Engineers |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310319808 |
| best_oa_location.source.host_organization_lineage_names | Institute of Electrical and Electronics Engineers |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://ieeexplore.ieee.org/ielx7/6287639/9312710/09369296.pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | IEEE Access |
| best_oa_location.landing_page_url | https://doi.org/10.1109/access.2021.3063736 |
| primary_location.id | doi:10.1109/access.2021.3063736 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2485537415 |
| primary_location.source.issn | 2169-3536 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2169-3536 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | IEEE Access |
| primary_location.source.host_organization | https://openalex.org/P4310319808 |
| primary_location.source.host_organization_name | Institute of Electrical and Electronics Engineers |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310319808 |
| primary_location.source.host_organization_lineage_names | Institute of Electrical and Electronics Engineers |
| primary_location.license | |
| primary_location.pdf_url | https://ieeexplore.ieee.org/ielx7/6287639/9312710/09369296.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | IEEE Access |
| primary_location.landing_page_url | https://doi.org/10.1109/access.2021.3063736 |
| publication_date | 2021-01-01 |
| publication_year | 2021 |
| referenced_works | https://openalex.org/W2919115771, https://openalex.org/W2957579702, https://openalex.org/W1993221720, https://openalex.org/W2492432421, https://openalex.org/W2979449653, https://openalex.org/W2737601558, https://openalex.org/W2791213346, https://openalex.org/W2766555361, https://openalex.org/W2807042118, https://openalex.org/W429766147, https://openalex.org/W2051812123, https://openalex.org/W2950674600, https://openalex.org/W2086705578, https://openalex.org/W3120338689, https://openalex.org/W2054824875, https://openalex.org/W3104401935, https://openalex.org/W2003019081, https://openalex.org/W2996713777, https://openalex.org/W2970865410, https://openalex.org/W2511358692, https://openalex.org/W2030509934, https://openalex.org/W2556842079, https://openalex.org/W2898516449, https://openalex.org/W2902454114, https://openalex.org/W2996046300, https://openalex.org/W2069796856, https://openalex.org/W2922480916, https://openalex.org/W2058443198, https://openalex.org/W2076669328, https://openalex.org/W2145094885, https://openalex.org/W2087177329, https://openalex.org/W2014610119, https://openalex.org/W2960005427, https://openalex.org/W2800501550, https://openalex.org/W3044457240, https://openalex.org/W3013782707, https://openalex.org/W2608649768, https://openalex.org/W2037124736, https://openalex.org/W4245419610, https://openalex.org/W2799857777, https://openalex.org/W2168234772, https://openalex.org/W2238951610, https://openalex.org/W2320998174, https://openalex.org/W2768098978, https://openalex.org/W1977934157, https://openalex.org/W3010818294, https://openalex.org/W2486405184, https://openalex.org/W1967996772, https://openalex.org/W2079805903, https://openalex.org/W2004725674, https://openalex.org/W3000389194, https://openalex.org/W2016236405, https://openalex.org/W2966040000, https://openalex.org/W2733974449, https://openalex.org/W2072397033, https://openalex.org/W2948488437, https://openalex.org/W2033038937, https://openalex.org/W2127165121, https://openalex.org/W2901307594, https://openalex.org/W353562331, https://openalex.org/W3016887452, https://openalex.org/W2923727767, https://openalex.org/W1833895844, https://openalex.org/W3133933462, https://openalex.org/W42578577, https://openalex.org/W3095866651, https://openalex.org/W598764262, https://openalex.org/W4248903018, https://openalex.org/W1582368210, https://openalex.org/W2005563629 |
| referenced_works_count | 70 |
| abstract_inverted_index.a | 129 |
| abstract_inverted_index.SH | 67 |
| abstract_inverted_index.We | 126 |
| abstract_inverted_index.by | 142 |
| abstract_inverted_index.in | 14, 79, 146 |
| abstract_inverted_index.is | 89 |
| abstract_inverted_index.of | 45, 57, 76, 85, 101, 138 |
| abstract_inverted_index.on | 21 |
| abstract_inverted_index.to | 9, 39, 61, 90, 109, 123 |
| abstract_inverted_index.30% | 143 |
| abstract_inverted_index.67% | 145 |
| abstract_inverted_index.The | 82 |
| abstract_inverted_index.and | 11, 18, 24, 42, 74, 144, 150 |
| abstract_inverted_index.due | 38 |
| abstract_inverted_index.for | 70, 113 |
| abstract_inverted_index.one | 29 |
| abstract_inverted_index.the | 22, 55, 63, 86, 99, 115, 135, 139 |
| abstract_inverted_index.two | 64 |
| abstract_inverted_index.use | 56 |
| abstract_inverted_index.(SH) | 2 |
| abstract_inverted_index.This | 52 |
| abstract_inverted_index.been | 6, 107, 121 |
| abstract_inverted_index.data | 119 |
| abstract_inverted_index.each | 46 |
| abstract_inverted_index.full | 130 |
| abstract_inverted_index.have | 5, 106, 120 |
| abstract_inverted_index.like | 16 |
| abstract_inverted_index.main | 83 |
| abstract_inverted_index.mode | 31, 40, 48, 93, 131 |
| abstract_inverted_index.more | 27 |
| abstract_inverted_index.rate | 137 |
| abstract_inverted_index.show | 91, 127 |
| abstract_inverted_index.size | 72, 148 |
| abstract_inverted_index.than | 28 |
| abstract_inverted_index.that | 92, 128 |
| abstract_inverted_index.time | 111 |
| abstract_inverted_index.used | 8, 122 |
| abstract_inverted_index.with | 50 |
| abstract_inverted_index.work | 88 |
| abstract_inverted_index.Shear | 0 |
| abstract_inverted_index.error | 136 |
| abstract_inverted_index.final | 140 |
| abstract_inverted_index.model | 141 |
| abstract_inverted_index.order | 66 |
| abstract_inverted_index.paper | 53 |
| abstract_inverted_index.plate | 25 |
| abstract_inverted_index.them. | 125 |
| abstract_inverted_index.waves | 4 |
| abstract_inverted_index.which | 33 |
| abstract_inverted_index.while | 117 |
| abstract_inverted_index.defect | 147 |
| abstract_inverted_index.detect | 12 |
| abstract_inverted_index.guided | 3, 68 |
| abstract_inverted_index.lowest | 65 |
| abstract_inverted_index.mixing | 41 |
| abstract_inverted_index.models | 60 |
| abstract_inverted_index.modes, | 69 |
| abstract_inverted_index.pipes. | 19 |
| abstract_inverted_index.plates | 17 |
| abstract_inverted_index.scheme | 133 |
| abstract_inverted_index.series | 112 |
| abstract_inverted_index.signal | 35 |
| abstract_inverted_index.analyse | 62 |
| abstract_inverted_index.complex | 43 |
| abstract_inverted_index.defects | 13, 78 |
| abstract_inverted_index.machine | 58, 96 |
| abstract_inverted_index.models. | 103 |
| abstract_inverted_index.plates. | 81 |
| abstract_inverted_index.present | 87 |
| abstract_inverted_index.renders | 34 |
| abstract_inverted_index.through | 95 |
| abstract_inverted_index.behavior | 44 |
| abstract_inverted_index.creating | 114 |
| abstract_inverted_index.defects. | 51 |
| abstract_inverted_index.estimate | 10 |
| abstract_inverted_index.generate | 110 |
| abstract_inverted_index.improves | 98 |
| abstract_inverted_index.learning | 59, 97 |
| abstract_inverted_index.validate | 124 |
| abstract_inverted_index.Depending | 20 |
| abstract_inverted_index.Numerical | 104 |
| abstract_inverted_index.aluminium | 80 |
| abstract_inverted_index.decreased | 134 |
| abstract_inverted_index.detection | 75, 151 |
| abstract_inverted_index.frequency | 23 |
| abstract_inverted_index.performed | 108 |
| abstract_inverted_index.Horizontal | 1 |
| abstract_inverted_index.estimation | 73, 149 |
| abstract_inverted_index.individual | 47 |
| abstract_inverted_index.predictive | 102 |
| abstract_inverted_index.separation | 94, 132 |
| abstract_inverted_index.structures | 15 |
| abstract_inverted_index.thickness, | 26 |
| abstract_inverted_index.complicated | 37 |
| abstract_inverted_index.estimators, | 116 |
| abstract_inverted_index.extensively | 7 |
| abstract_inverted_index.guided-wave | 30 |
| abstract_inverted_index.interacting | 49 |
| abstract_inverted_index.propagates, | 32 |
| abstract_inverted_index.simulations | 105 |
| abstract_inverted_index.contribution | 84 |
| abstract_inverted_index.experimental | 118 |
| abstract_inverted_index.investigates | 54 |
| abstract_inverted_index.quantitative | 71 |
| abstract_inverted_index.effectiveness | 100 |
| abstract_inverted_index.respectively. | 152 |
| abstract_inverted_index.corrosion-like | 77 |
| abstract_inverted_index.interpretation | 36 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 93 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.86372418 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |