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

Project 3.19 Summary:

The 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. Material aging and structural deterioration of selected candidate structures (e.g.,
highway bridges) will be frequently (from twice a day to once a week) inspected to develop large
amount of sensor data for condition assessment using machine learning. The problem is important
because, with frequent inspection of civil infrastructure systems, processing and visualization of
large amount of multiple-format sensor data have become a challenging task at the system’s level
for bridge engineers. Registration of 2D photographs and sensor images in a 3D environment aided
with VR equipment (e.g., headsets, handles, controllers) can help bridge engineers to better register
inspection and monitoring data in multiple formats (e.g., photographs, images, texts, sketches) to
actual structures. Frequent inspection of structures can produce large amount of data required by
machine learning, as well as capturing the weekly, monthly, and seasonal changes of
background/baseline information. In this base funded project, we propose to 1) collect
electromagnetic (EM) (e.g., optical, radar, and laser sensors) and mechanical (e.g., impact-echo,
ultrasonic testing, pulse tomography sensors) sensor data on a frequent basis (from twice a day to
once a week) to develop large amount of data for machine learning interpretation, 2) study the
effect of material aging on structural deterioration of highway bridges, and 3) develop a VR
platform for rendering sensor data (including bridge rating and inspection reports) of inspected
bridges in a 3D environment for the convenient interpretation of sensor data.

Sponsors:
Office of the Assistant Secretary for Research and Technology, University Transportation Centers Program, Department of Transportation, MassDOT.

Implementation of Research Outcomes:
This project is in its initial research phase. Implementation of Research outcomes will be reported upon completion of initial research.

Impacts and Benefits of Implementation:
This project is in its initial research phase. Impacts and benefits of the research will be reported after the implementation phase.

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