The invention provides an LVR
evaporation system control method and
system based on an intelligent
algorithm, and relates to the field of low-vacuum
reboiler control. According to the method, temperature sensors,
vacuum pressure sensors,
conductivity sensors,
turbidity sensors and liquid level sensors are arranged on an
evaporator, a circulating pipeline and a vacuum
system, and a scaling risk state sensing model is constructed; calculating a
supersaturation index SI based on the acquired
signal and soft measurement, and judging and identifying a metastable or critical deposition working condition through a threshold value; performing
risk level classification on the multi-dimensional
state vector by using a
reinforcement learning algorithm (PPO), and outputting risk confidence and a trigger
signal; after the risk is triggered, bypass induced
nucleation is realized through PID shunt control, and the shunt proportion, the bypass
temperature difference and the stirring intensity are accurately adjusted; meanwhile, a strategy optimization module is introduced, and self-adaptive updating of a control strategy is achieved through a
return function and an online training mechanism; and finally, long-period stable operation and low scaling rate of the
evaporation system are realized through
hysteresis control and an
energy consumption self-optimization mechanism.