Multi-Domain Modeling and Analysis of Marine Steam Power System Based on Digital Twin

Abstract

The marine steam power system includes a large amount of thermal equipment; meanwhile, the marine environment is harsh and the working conditions change frequently. Operation management involves many disciplines, such as heat, machinery, control, electricity, etc. It is a complex multi-discipline physical system with typical nonlinear, multi-parameter, strong coupling characteristics. In order to realize the health management of a marine steam power system, based on digital twin technology combined with the Modelica language, modular modeling, etc., this paper conducts in-depth research on the multi-domain modeling of the marine steam power system, characteristic analysis of variable working conditions, fault simulation, etc. The analysis results show that the dynamic response trend of the model is consistent with the actual operation, the error of the main steam flow at 1800 s is the largest and is −4.9%, and the error of the main steam flow, steam turbine output power, cooling water outlet temperature and other key parameters is within ±5%. Virtual reality mapping between the digital model and the physical equipment is realized, which lays a foundation for mastering the dynamic characteristics of the marine steam power system.

Artificial Neural Network Model for Temperature Prediction and Regulation during Molten Steel Transportation Process

“…In the iron and steel industries, many metallurgical scholars have begun to focus their research on the intelligent control of metallurgical processes [19][20][21][22][23][24][25][26]. The artificial neural network model is widely used in the prediction of working conditions, such as head warpage [27], composition prediction [28], intermediate ladle steel flow characteristics [29], elemental content [30], data acquisition [31], the prediction of flame characteristics [32], and crack detection [33].…”