Bridge Monitoring Through a Hybrid Approach Leveraging a Modal Updating Technique and an Artificial Intelligence (AI) Method [Research Brief]

Cho, Chunhee; Moon, DoSoo; Pacific Southwest Region 9 UTC, University of Southern California; METRANS Transportation Center (Calif.); University of Hawaii at Manoa

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Bridge Monitoring Through a Hybrid Approach Leveraging a Modal Updating Technique and an Artificial Intelligence (AI) Method [Research Brief]

2022-08-01
By Cho, Chunhee ; Moon, DoSoo

[PDF-227.21 KB]

English

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Creators:

Cho, Chunhee ; Moon, DoSoo

Cho, Chunhee ; Moon, DoSoo Less -
Corporate Creators:

Pacific Southwest Region 9 UTC, University of Southern California ; METRANS Transportation Center (Calif.) ; University of Hawaii at Manoa

Pacific Southwest Region 9 UTC, University of Southern California ; METRANS Transportation Center (Calif.) ; University of Hawaii at Manoa Less -
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology Less -
Subject/TRT Terms:

[+]

Bridges Detection And Identification System Applications Machine Learning Predictive Models Structural Deterioration And Defects Structural Health Monitoring
Resource Type:

Brief
Geographical Coverage:

United States
Edition:

Research Brief
Corporate Publisher:

METRANS Transportation Center (Calif.)
Abstract:

The objective of this project is to develop a post processing damage detecting algorithm by leveraging a modal updating technique and an artificial intelligence (AI) method. Problem Statement: The proposed project integrated two methods (i.e., a model updating technique and a data-driven prediction method) that can compensate for each other’s the weakness that otherwise imposed difficulty in precise real-time application of health monitoring systems. This project leveraged a mode updating technique with high-fidelity experimental data to obtain an accurate digital model that represents an actual bridge. The drawback of the model updating technique (i.e., high computational time) can be overcome by applying a data-drive method that is known to be computationally efficient. The proposed approach will then result in a fast and accurate method (i.e., a model-based data-driven method) for early damage identification of bridge structures.
Format:

PDF
Funding:

USDOT Grant 69A3551747109
Collection(s):

University Transportation Centers
Main Document Checksum:

[+]

urn:sha256:f79ff49f5d8e4accbe4209567e0cb02108e2bdf78c7b7639f2c7a95dfd35d3c6
Download URL:

https://rosap.ntl.bts.gov/view/dot/67552/dot_67552_DS1.pdf
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Bridge Monitoring Through a Hybrid Approach Leveraging a Modal Updating Technique and an Artificial Intelligence (AI) Method [Research Brief]

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