Condition Diagnosis of Long-Span Bridge Pile Foundations Based on the Spatial Correlation of High-Density Strain Measurement Points
Pile foundations of long-span bridges are often deeply buried in soil, and their structural condition is difficult to accurately diagnose by conventional methods. To address this issue, a method for diagnosing the structural condition of bridge pile foundations based on the spatial correlation of hi...
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MDPI AG
2021
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oai:doaj.org-article:8db3d55910904b68969dd0308dd15c022021-11-25T19:01:48ZCondition Diagnosis of Long-Span Bridge Pile Foundations Based on the Spatial Correlation of High-Density Strain Measurement Points10.3390/su1322124982071-1050https://doaj.org/article/8db3d55910904b68969dd0308dd15c022021-11-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/22/12498https://doaj.org/toc/2071-1050Pile foundations of long-span bridges are often deeply buried in soil, and their structural condition is difficult to accurately diagnose by conventional methods. To address this issue, a method for diagnosing the structural condition of bridge pile foundations based on the spatial correlation of high-density strain measurement points is proposed. The strain data of the high-density measurement points of a bridge pile foundation are obtained by using distributed optical fiber sensing technology based on Brillouin scattering, and then an algorithm for diagnosing the structural condition of the pile foundation based on geographically weighted regression analysis is presented. On this basis, aiming at the scour of the pile foundation of long-span bridges, an algorithm for estimating the scour depth of the pile foundation based on sliding plane clustering is proposed. Finally, the effectiveness of the proposed method is verified by numerical simulation and actual bridge data.Feng LiuQianen XuYang LiuMDPI AGarticlebridge pile foundationsstructural condition assessmentgeographically weighted regressioncluster analysisdistributed optical fiber sensing techniqueEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 12498, p 12498 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
bridge pile foundations structural condition assessment geographically weighted regression cluster analysis distributed optical fiber sensing technique Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 |
| spellingShingle |
bridge pile foundations structural condition assessment geographically weighted regression cluster analysis distributed optical fiber sensing technique Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Feng Liu Qianen Xu Yang Liu Condition Diagnosis of Long-Span Bridge Pile Foundations Based on the Spatial Correlation of High-Density Strain Measurement Points |
| description |
Pile foundations of long-span bridges are often deeply buried in soil, and their structural condition is difficult to accurately diagnose by conventional methods. To address this issue, a method for diagnosing the structural condition of bridge pile foundations based on the spatial correlation of high-density strain measurement points is proposed. The strain data of the high-density measurement points of a bridge pile foundation are obtained by using distributed optical fiber sensing technology based on Brillouin scattering, and then an algorithm for diagnosing the structural condition of the pile foundation based on geographically weighted regression analysis is presented. On this basis, aiming at the scour of the pile foundation of long-span bridges, an algorithm for estimating the scour depth of the pile foundation based on sliding plane clustering is proposed. Finally, the effectiveness of the proposed method is verified by numerical simulation and actual bridge data. |
| format |
article |
| author |
Feng Liu Qianen Xu Yang Liu |
| author_facet |
Feng Liu Qianen Xu Yang Liu |
| author_sort |
Feng Liu |
| title |
Condition Diagnosis of Long-Span Bridge Pile Foundations Based on the Spatial Correlation of High-Density Strain Measurement Points |
| title_short |
Condition Diagnosis of Long-Span Bridge Pile Foundations Based on the Spatial Correlation of High-Density Strain Measurement Points |
| title_full |
Condition Diagnosis of Long-Span Bridge Pile Foundations Based on the Spatial Correlation of High-Density Strain Measurement Points |
| title_fullStr |
Condition Diagnosis of Long-Span Bridge Pile Foundations Based on the Spatial Correlation of High-Density Strain Measurement Points |
| title_full_unstemmed |
Condition Diagnosis of Long-Span Bridge Pile Foundations Based on the Spatial Correlation of High-Density Strain Measurement Points |
| title_sort |
condition diagnosis of long-span bridge pile foundations based on the spatial correlation of high-density strain measurement points |
| publisher |
MDPI AG |
| publishDate |
2021 |
| url |
https://doaj.org/article/8db3d55910904b68969dd0308dd15c02 |
| work_keys_str_mv |
AT fengliu conditiondiagnosisoflongspanbridgepilefoundationsbasedonthespatialcorrelationofhighdensitystrainmeasurementpoints AT qianenxu conditiondiagnosisoflongspanbridgepilefoundationsbasedonthespatialcorrelationofhighdensitystrainmeasurementpoints AT yangliu conditiondiagnosisoflongspanbridgepilefoundationsbasedonthespatialcorrelationofhighdensitystrainmeasurementpoints |
| _version_ |
1718410416380444672 |