The invention discloses a pepper harvester advancing speed two-stage regulation and control method based on a multi-source prediction model, and mainly relates to the field of pepper harvesters. The method comprises the steps that a high-speed camera and a
torque sensor collect image information and a torque
signal, the image information and the torque
signal are preprocessed and then input into a
machine vision model and a torque prediction model to obtain a predicted torque value corrected by an
image processing technology, and after the predicted roller load condition is obtained through a mechanical model, the
forward speed is preliminarily adjusted to enable the load to be in a normal value interval; load data on an upper
conveyor belt and a lower
conveyor belt of a separation device are collected, after the
impurity rate is calculated, the
impurity rate is input into a CNN-LSTM neural
network model constructed by fusion time and space features improved by an
ant colony
algorithm to obtain the harvesting
impurity rate condition, and after the advancing speed is further adjusted according to the predicted impurity rate, the load condition is monitored in real time. The speed regulation of the load condition in the two-stage speed regulation is prior to the speed regulation of the impurity rate condition. According to the invention, the
forward speed of the harvester can be adjusted in real time according to the conditions of the roller load and the harvesting impurity rate.