Automated Diagnostic System for Remote Monitoring of a Concrete Dam

Structural Health Monitoring (SHM) has tremendous potential to detect incipient structural failures in various components, e.g., onset of fatigue damage, corrosion, spalling and delamination in the structures during their service life, so that preventive actions can be employed in a timely manner. St. Clair Region Conservation Authority (SCRCA) has felt immediate need for real-time monitoring of W. Darcy McKeough Floodway, one of the flood control dams that has been subjected to fluctuating operational conditions, adverse weather and climate change over many years. The dam is consisted of an earth fill embankment, concrete control structure housing two sluice gates and a diversion channel. Real-time detailed monitoring of the embankment, sluice gates and diversion channel is of paramount importance to avoid water seepage and future flooding issues. Main objective of this project is to develop automated diagnostic system for remote inspection of the concrete dam by harnessing machine learning techniques.

Intern: 
Mohamed Barbosh
Faculty Supervisor: 
Ayan Sadhu
Province: 
Ontario
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