Early Warning of Internal Leakage in Heat Exchanger Network Based on Dynamic Mechanism Model and Long Short-Term Memory Method

In the process of butadiene rubber production, internal leakage occurs in heat exchangers due to excessive pressure difference. It leads considerable flow organic matters into circulating water system. Since these are volatile and prone explode cold tower, is potentially dangerous for enterprise. To prevent this phenomenon, a novel intelligent early warning risk assessment method (DYN-EW-QRA) proposed paper by combining dynamic simulations (DYN), long short-term memory (LSTM), quantitative (QRA). First, an original mechanism model exchanger network designed simulated DYN obtain datasets. Second, potential relationships between variables that have direct impact on hazards accident deeply learned LSTM predict trends. Finally, QRA used analyze range destructive power hazards. The results show DYN-EW-QRA has excellent performance.