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