One of the largest power transmitters in North America, located in Ontario, completed a multiyear corrosion study to verify the corrosion rate models for zinc and steel.
As a result of the initial study which included accelerated aging tests, a long term field corrosion monitoring program was initiated. One hundred and twenty five corrosion monitoring sites (CMS) were selected across the province. The coupons of 100 sites were installed at top and mid height of the towers. These coupons and their supporting racks are grounded to mimic the actual condition of the steel members of transmission towers. The coupons of the remaining 25 sites were installed on the towers at lower elevations (3-5m AGL). These coupons were completely insulated from the tower to study whether electrostatic induction has any effect on corrosion rate or not.
To manage this large network of corrosion monitoring sites, the authors have developed an advanced corrosion database management system (ACDMS). This system was enhanced with intelligent software for image analysis using a learning scheme to recognize corrosion type and corrosion severity by analysing digital images of the corroded steel coupons or members. The data from the corrosion monitoring sites are expected to provide our transmission engineers with valuable information to improve the damage assessment, repair, refurbishment, and maintenance of existing steel transmission structures. In addition, this information is expected to help improve the accuracy of corrosion models and the image analysis software.
Key words: corrosion, steel coupons, corrosion monitoring sites, neural networks, image analysis.