Determination of a Procedure for Monitoring Sacrificial Cathodic Protection Systems for Aboveground Steel Storage Tanks
Open Access
- Author:
- Meley, January Linn
- Graduate Program:
- Civil Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- September 19, 2006
- Committee Members:
- Dr Andrea Schokker, Committee Chair/Co-Chair
Jeffrey A Laman, Committee Member
Dr Daniel Linzell, Committee Member
Dr Sunil Sinha, Committee Member
Howard W Pickering, Committee Member - Keywords:
- Cathodic Protection
Neural Networks
Aboveground Storage Tanks - Abstract:
- The main objective of this research was to develop a procedure for monitoring sacrificial cathodic protection systems that have been installed under steel aboveground storage tanks. The procedure was to include a method that would account for the IR drops, or potential losses, in the system. Once the losses are accounted for, a direct comparison to the required –850mV between the tank and the copper – to – copper sulfate (Cu/CuSO4) reference electrode can be made. This comparison will determine if the systems are providing the required protection for the storage tank. The first step in accomplishing this goal was to formulate a list of variables that are thought to affect the potential losses in the system. Once completed, the task of building an experimental setup that facilitated the measurement of each of these variables became important. Many data sets, 288 specifically, were recorded using this controlled test setup. Measurements were taken during all seasons of the year and during all types of weather and temperatures, mirroring real world conditions. Field data was also obtained using existing cathodic protection systems located in facilities across Pennsylvania and Ohio. Once all the data had been collected, appropriate files were created for use in a neural networking program. Eighty percent of the experimental data was used to train the system while the remaining twenty percent was used to test the system. After the final weights had been calculated by the network, the field data was tested in the network. The output became the adjusted voltage which could be directly compared to the required –850mV. The back propagation neural network chosen for this project proved to be very useful. The network outputs of the training and testing phases were all within 4% of the actual outputs measured using the experimental tank. When the field data was tested with the network most of the systems were providing more protection than required which confirms the belief that the cathodic systems are indeed working as intended.