Research on optimizing PI parameter of skin effect electric trace heating system based on deep learning

In the pipeline transportation of petroleum, electric heat tracing system is needed to ensure the normal flow of petroleum. The heating efficiency is directly related to the PI parameters of the system.At the same time, if the pressure in the pipeline is not taken into consideration when designing the system , it is easy for the excessive pressure to threaten the normal operation. To solve these problem, this paper proposes to optimize the subject PI parameters of the system, modulate the PI parameters to reduce the pressure when the pressure is high, then apply them to the skin effect electric heat tracing system.