中文摘要：

为解决花生收获过程中产量监测问题，结合4HBLZ一2型自走式花生联合收获机设计了一种智能测产系统。硬件部分包括北斗导航车载接收系统、单片微处理器及重量传感器、德国麦希欧接触式在线水分传感器，通过CAN总线接口与上位机连接。将定量称重与网格细分技术相结合应用于收获机测产领域，相较于冲量式测产系统，极大地降低了收获机振动引起的产量累积误差。软件采用跨平台应用程序Qt完成了各传感器数据的实时接收、存储，以及对任意划定地块产量数据的查询，并且能够实现查询产量数据的平面及3D立体渐变色显示。在5种不同工况下对该测产系统进行试验，测试花生收获机工作状态下测产系统的稳定性。在发动机大油门、开动夹持输送装置工况下，产量相对误差绝对值小于2％，在田间试验情况下产量相对误差绝对值小于5％。

英文摘要：

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.