摘要
针对联合收获机在收获高产水稻时籽粒夹带损失率偏高,籽粒夹带损失实时直接测量难度大的问题,该文提出了一种对纵轴流联合收获机籽粒夹带损失进行实时间接检测的新方法。试验研究了不同喂入量下纵轴流滚筒下脱出混合物中籽粒沿滚筒纵向与横向的分布规律,推导了籽粒沿纵轴流脱粒滚筒径向、轴向的分离概率模型并建立了籽粒夹带损失间接监测数学模型。为准确获取籽粒碰撞信息,试验研究了不同压电材料下籽粒碰撞输出信号特征及籽粒与不同材料敏感板间的碰撞过程,以此为基础研制了性能优良的籽粒损失监测传感器并对其进行了隔振结构设计。将研制的籽粒损失监测传感器安装到纵轴流联合收获机上,运用籽粒夹带损失间接监测方法进行了田间试验,试验结果表明,该文提出的籽粒夹带损失监测方法切实可行,研制的籽粒损失监测传感器工作性能稳定、准确,收获高产水稻时籽粒夹带损失最大测量相对误差为3.03%。该文的研究实现了籽粒夹带损失的实时自动监测,为工程实际运用奠定了良好的基础。
The ratio of the separation loss was an important indicator to measure the operating performance of a combine harvester, and it also was an important criterion to adjust the relevant operating parameters. It was hard to monitor the separation loss directly for a combine harvester when harvesting high-yielding rice. To monitor the separation loss in real time, this paper promoted a new method to monitor the separation loss. The method mainly included the following steps： draw distribution functions of separated grain in an axial direction of a threshing rotor in a laboratory test-rig and select a proper detecting area under the separating concave; then establish a mathematical model among relevant variables; develop a grain detecting sensor which could discriminate free grains from MOG; and fix the sensor on a combine harvester, based on the detecting mathematical model to calculate grain separation loss in real time. To achieve this purpose, a threshing-separation experiment was carried out in an axial threshing-separating-cleaning test-bed, which selected Wu ＂2645＂ rice as test materials. In addition, the vertical and horizontal distribution of the mixed material under the longitudinal-axial drum was studied with different feeding quantity. More detailed comparative analysis and research was carried out on different feeding quantity, deriving the separation probability model along the radial and axial direction of the longitudinal axial of the flow threshing drum, and establishing an indirectly monitoring mathematical model of separation loss. The accuracy of the grain loss monitoring sensor was the key to accurately measuring the grain flow in the monitoring area. To obtain the grain detecting signal effectively, high-sensitivity receiver material piezoelectric ceramic YT-5 and PVDF films were selected as sensitive components, and a signal process circuit which was composed of voltage amplifier, band-pass filter, precision full-wave rectification, envelope detector to measure the grain impact signal and a secondary instrument which used AT89C52 microcontroller as the core chip were developed to acquire the grain impact signal, a collision signal that had been studied according to comparative collision test; an ellipsoid particle model was established according to the physical properties of rice grain and used the discrete element method, which used Hertz-Mindlin to model as a contact mechanics model, to simulate the impact process of a grain with a detection sensor, which provided a basic reference for selecting the sensitive plate, and one-degree freedom vibration isolation was incorporated in the sensor to eliminate the influence of the combine harvester＇s vibration. The grain loss monitoring sensor was installed on the combine harvester utilizing the indirect monitoring method which was promoted in this paper to detect separation loss in the field working process. Field test results showed that the separation loss monitoring method was feasible, and the performance of the grain loss monitor sensor was stable. The biggest measurement relative error of the separation losses was 3.03% when harvesting rice. The study of this paper realized real-time monitoring grain separation loss, which laid a good foundation for a practical engineering application.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2014年第3期18-26,共9页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家高技术研究发展计划(863计划)资助项目(2012AA10A502)
江苏省科技支撑计划资助项目(BE2012382
BE2012312)
江苏省高校自然科学研究资助项目(11KJA460002)
江苏高校优势学科建设工程资助项目(苏财教(2011)8号)
关键词
传感器
监测
联合收获机
农业工程
夹带损失
性能试验
sensors
monitonng
combines
agricultural engineering
grain separation loss
pertbrmanceexperiment
