3.19 Detection and Monitoring of Material Aging and Structural Deterioration Using Electromagnetic and Mechanical Sensors with Virtual Reality and Machine Learning Modeling

Yu, Tzuyang; Wei, Jianqiang

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3.19 Detection and Monitoring of Material Aging and Structural Deterioration Using Electromagnetic and Mechanical Sensors with Virtual Reality and Machine Learning Modeling

2025-09-30
By Yu, Tzuyang ; Wei, Jianqiang

File Language:

English

Details

Creators:

Yu, Tzuyang ; Wei, Jianqiang
Corporate Creators:

University of Massachusetts at Lowell ; University of Maine. Transportation Infrastructure Durability Center (TIDC)
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
Subject/TRT Terms:

Aging (Materials) Data Analysis Detection And Identification Electromagnetic Devices Environmental Impact Analysis Infrastructure Machine Learning Monitoring Sensors Structural Deterioration And Defects Virtual Reality Visualization
Publication/ Report Number:

3.19
Resource Type:

Tech Report
Geographical Coverage:

United States ; Massachusetts ; New England
Edition:

Final Report: 01/01/2022 - 09/30/2025
Corporate Publisher:

University of Maine. Transportation Infrastructure Durability Center (TIDC)
Abstract:

The research problem we are trying to solve is the detection and monitoring of aging civil infrastructure components and systems in New England by using visual information and subsurface images in a virtual reality (VR) environment for data visualization and machine learning (ML) for data interpretation. The overall research objective is to study the detection and monitoring problem of aging civil infrastructure components and systems in New England by using visual information and subsurface images in a virtual reality (VR) environment for data visualization and machine learning (ML) for data interpretation.
Format:

PDF
Collection(s):

US Transportation Collection
Main Document Checksum:

urn:sha-512:fee667310f8fdf7db1c79c8ac5cb8550247f33a57bb1ad41e9c0784369ea48aeb7325991f8d8d96009ed789e121dd032d6017f9782042e9e9ed8f1ba84d8c4b0
Download URL:

https://rosap.ntl.bts.gov/view/dot/88856/dot_88856_DS1.pdf
File Type:

[PDF - 4.32 MB ]

File Language:

English

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