Damage detection of frame structure using a novel time-domain regression method Article Swipe
Xingle Ji
,
Xueyong Xu
,
Kun Huang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-4098093/v1
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-4098093/v1
Shear structure model is the most frequently used to model for the damage detection of frame building structures. However, due to the existence of modelling error, using a shear structure model to perform damage detection of a complex frame structure often results in inaccurate detection results. In this paper, a novel reduced model for the frame is proposed, which converts a multi-story multi-bay plane frame into a beam-like model, having one translational and two rotational degrees-of-freedom for each floor. Based on the new model, a novel time-domain regression method (TDRM) was established using the spectral density function between the horizontal acceleration of the frame floor and the reference response to identify the equivalent layer stiffness and damping parameters. Finally, a five-story two-bay frame structure is used to demonstrate the efficacy of the proposed time-domain regression method of estimating structural parameters and identifying structural damage.The results show that this method can identify, locate, and quantify the structural stiffness changes accurately.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-4098093/v1
- https://www.researchsquare.com/article/rs-4098093/latest.pdf
- OA Status
- green
- References
- 26
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4393228922
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- OpenAlex ID
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https://openalex.org/W4393228922Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-4098093/v1Digital Object Identifier
- Title
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Damage detection of frame structure using a novel time-domain regression methodWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-03-27Full publication date if available
- Authors
-
Xingle Ji, Xueyong Xu, Kun HuangList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-4098093/v1Publisher landing page
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https://www.researchsquare.com/article/rs-4098093/latest.pdfDirect link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.researchsquare.com/article/rs-4098093/latest.pdfDirect OA link when available
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Frame (networking), Regression, Computer science, Domain (mathematical analysis), Regression analysis, Artificial intelligence, Statistics, Data mining, Econometrics, Mathematics, Machine learning, Telecommunications, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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26Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.quantify | 154 |
| abstract_inverted_index.response | 109 |
| abstract_inverted_index.results. | 46 |
| abstract_inverted_index.spectral | 95 |
| abstract_inverted_index.beam-like | 68 |
| abstract_inverted_index.detection | 14, 35, 45 |
| abstract_inverted_index.existence | 23 |
| abstract_inverted_index.identify, | 151 |
| abstract_inverted_index.modelling | 25 |
| abstract_inverted_index.multi-bay | 63 |
| abstract_inverted_index.proposed, | 58 |
| abstract_inverted_index.reference | 108 |
| abstract_inverted_index.stiffness | 115, 157 |
| abstract_inverted_index.structure | 2, 30, 40, 124 |
| abstract_inverted_index.damage.The | 144 |
| abstract_inverted_index.equivalent | 113 |
| abstract_inverted_index.estimating | 138 |
| abstract_inverted_index.five-story | 121 |
| abstract_inverted_index.frequently | 7 |
| abstract_inverted_index.horizontal | 100 |
| abstract_inverted_index.inaccurate | 44 |
| abstract_inverted_index.parameters | 140 |
| abstract_inverted_index.regression | 88, 135 |
| abstract_inverted_index.rotational | 75 |
| abstract_inverted_index.structural | 139, 143, 156 |
| abstract_inverted_index.accurately. | 159 |
| abstract_inverted_index.demonstrate | 128 |
| abstract_inverted_index.established | 92 |
| abstract_inverted_index.identifying | 142 |
| abstract_inverted_index.multi-story | 62 |
| abstract_inverted_index.parameters. | 118 |
| abstract_inverted_index.structures. | 18 |
| abstract_inverted_index.time-domain | 87, 134 |
| abstract_inverted_index.acceleration | 101 |
| abstract_inverted_index.translational | 72 |
| abstract_inverted_index.degrees-of-freedom | 76 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5104341696 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I3018263800, https://openalex.org/I4210087590 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.5899999737739563 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.05170906 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |