The intelligent
temperature control self-adaptive reaction kettle cleaning method comprises the following steps: firstly, carrying out
system preparation and initialization, and setting cleaning parameters and
reinforcement learning algorithm parameters; positioning and detecting the reaction kettle, and obtaining the
pollution degree of the inner wall as an initial state input; then the
intelligent control system determines the temperature, the
reinforcement learning algorithm adjusts the temperature according to the state, the controller is used for controlling the heating coil to heat, and the temperature is accurately controlled through the PID
algorithm; then starting a washing mechanism to clean the reaction kettle, adjusting the rotating speed of the washing mechanism according to the cleaning state through a
reinforcement learning algorithm, spraying heated cleaning liquid by a water pump to cooperate with cleaning, monitoring the cleaning effect,
temperature and pressure in real time in the cleaning process, and adjusting a cleaning strategy through the
reinforcement learning algorithm according to feedback information; and finally, the
intelligent control system judges that cleaning is finished, equipment is reset, the reaction kettle is cleaned, checked and dried, and cleaning data is recorded for subsequent analysis and optimization. The self-adaptive cleaning is realized through a
reinforcement learning algorithm, and the cleaning quality and the
safe operation of the system can be ensured.