In order to solve the problem of yield monitoring during peanut harvesting, aiming at 4HBLZ-2 type selfpropelled peanut combine harvester, an intelligent yield monitoring system was designed. Hardware part included Beidou satellite positioning system, the single chip microprocessor, weight sensor and German ACO contact online moisture sensor; it was connected to the host computer through CAN bus interface. Weighing controller adopted 24bit A/D converter with high precision and digital filter algorithm to ensure the accuracy of weighing data working under vibration environment in the field. Quantitative weighing and mesh subdivision technique were applied to harvester yield monitoring field in this system for the first time, compared with impactbased yield monitoring system, it could reduce more accumulative error caused by peanut harvester vibration working in the field. Software part adopted crossplatform application Qt to achieve the data realtime reception and storage of different sensors, then Beidou data and yield data were processed, and it adopted the way of accumulating different harvesting block yields to establish the mathematical model. The software could query yield data in arbitrary setting blocks, and also realize plane displaying and 3D stereoscopic gradient color displaying. In order to test the stability of yield monitoring system of peanut harvester under working state, yield monitoring system performed vibration test under five different conditions. The absolute relative error of yield was below 2% in condition No.4 in laboratory and below 5% in field.