Date of Award

1-10-2024

Publication Type

Thesis

Degree Name

M.A.Sc.

Department

Civil and Environmental Engineering

Keywords

autonomous, calibration, corrosion measurement, image assessment, protocol parameters, proxy part

Supervisor

Edwin Tam

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Corrosion measurement of digital images is an important method for determining the effectiveness of corrosion prevention products. In mobile transportation applications, long periods of time may pass before the vehicle is imaged again. This research develops a field image acquisition and processing protocol for a corrosion detection software algorithm, already proven to successfully detect various types of corrosion, to standardize and optimize corrosion detection in digital images and ensure consistent, reliable, and comparable results can be obtained over time. Corrosion on the vehicle underside was imaged and measured in the lab to develop the data gathering parameters required for results uniformity. The angle and distance that produce the least issues with respect to interference, while providing clear and simple imaging and ease of use in the field were ascertained to be 90 degrees from the optical plane and 65cm. The requirement of flash photography for optimal results was also proven. In addition, the proxy part with the least variation in corrosion measurement that is easiest to access and capture was identified as the front crossmember. The mathematical relationship of the object area represented by each pixel to camera distance from the object was also established as a power equation, which provides rapid corrosion area quantification in cm2. This calibration equation replaces the manual Area Calibration Factor (ACF) gathering process, removes human influence and enables employment of onboard distance sensors for image acquisition automation in the future.

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