DC power supply based on artificial neural networks used in cathodic protection for water carrying pipeline for electricity station.

This paper presents a proposed design and investigation of an impressed current and Single-Ended Primary Inductive Converter (SEPIC) converter based on an artificial neural network to assess the potential difference required to control cathodic protection system. The cathodic protection methods proved their effectiveness in the metallic equipment protection in the industrial applications that contain liquids and that are buried in electrolyte mediums against the electrochemical corrosion process, where D.C power supply plays an important role in the cathodic protection system. The proposed design consists of an intelligent d.c power supply and a group of anodes. This model has been adjusted to be able to equalize the normal voltage difference between the surrounding medium and the metal part being protected. The proposed design has been tested and investigated the cooling water carrying pipeline of AL-Quds electrical power station as a part of the unified Iraqi power network. The protection voltages and currents were calculated with a permissible tolerance based on; the pipeline characteristics, its coating, and the buried soil along the pipeline length to ensure better performance of protection. The obtained experimental and simulation results showed high effectiveness and accuracy by maintains the negative potential of the pipeline within the permissible and standard limits of the Iron metal of the pipeline. [ABSTRACT FROM AUTHOR]