气吸式大豆精密排种器排种性能试验研究

在精密播种机中,精密排种器是其工作的核心部件,工作性能直接制约了播种机播种性能的优劣。为了探究影响气吸式排种器工作性能的主次因素,以大豆气吸式排种器为研究对象进行了台架性能试验测试。试验确定排种盘转速为影响排种器排种性能的主次因素,气室负压为次要因素;排种盘转速为20 r/min,气室负压为5 k Pa时该大豆气吸式排种器排种性能最优,合格指数高达91.13%。该研究结果对排种器结构改进以及性能优化提供了参考依据。     

刨花计量料仓在刨花板生产中的应用

分别从工艺流程、结构和工作原理以及使用中的注意事项等方面介绍了刨花计量料仓在刨花板生产线中施胶前及铺装前的应用情况。     

国内气力式玉米精量排种器研究进展

近年来，我国机械化技术水平不断提高，精量播种正逐步取代传统的粗放式播种，从而降低了种植成本，同时提高了生产效率和利润。目前，我国玉米单产水平存在较大提升空间，提升玉米机械播种水平是提高玉米播种质量和增加产量的有效方式。本文对气力式玉米精量排种器的研究现状进行了综述，包括气吸式、气吹式和气压式3种类型，分别总结了其结构、工作原理和工作参数、性能、优势等，评述了试验效果；针对玉米精量排种器目前存在的问题进行了分析，并提出了未来的发展趋势，以期为促进玉米机械化生产提供参考。     

气吸式打瓜穴播器对不同尺寸种子排种适应性的研究

针对气吸式打瓜穴播器(新疆石河子科神公司研制)排种适应性差这一问题,以新疆主要种植的打瓜品种—内蒙大片、内蒙中片、内蒙小片为试验材料,应用正交试验设计的方法,分析了打瓜品种类型、取种盘转速、负压室压力对穴播器排种适应性的影响。试验结果确定了影响穴播器排种适应性因素的主次顺序,以及穴播器排种适应性的最优工作参数组合。     

隔膜计量泵的改良设计与汽蚀性能的提高

针对应用于石油化工装置上的进口隔膜计量泵容易产生的汽蚀问题，对隔膜泵复合隔膜、柱塞密封副、液压平衡与补偿阀结构进行了改良设计，采用较大承载能力的机座、独特阶梯式活塞、加大直径的活塞、PTFE＋NBR复合隔膜，改良放气安全阀及油浸没式补偿系统等方法，提高了隔膜计量泵的汽蚀性能；通过对改造的隔膜计量泵与原有的计量泵进行的汽蚀试验对比，给出了隔膜计量泵性能与现场使用的最佳匹配工况。改良的结构设计和新型材料的选用大大提高了计量泵的汽蚀性能。     

内窝孔式棉花精量穴播轮的试验

目前,新疆棉花种植广泛采用半精量穴播轮,其原理是勺式取种,存在下种量大、重播率高、下种不均匀、后续工作量大等缺陷,已不适应当前棉花产业发展要求。气吸式精量穴播轮可实现一穴一粒,准确率高,但气吸式棉花穴播机结构复杂、造价高,对机具维护、使用者技能以及整地有较高要求。另外,作业时拖拉机须保持高速运转,能源消耗大,因而限制了气吸式精量穴播轮的普及和推广。为此,将内窝孔取种原理应用于棉花精量取种,介绍了内窝孔式穴播轮的结构和工作过程,并进行了排种试验和分析。由试验得知,内窝孔式取种原理可用于新疆棉花的精量取种。     

精密排种器性能指标检测统计计算软件开发与应用

针对精密排种器性能指标统计分析中存在统计计算工作量大,且为重复性工作,人工计算耗时多,又难以保证计算准确性和结果可靠性的现实问题,研究开发了一种基于Visual C 能实现与Excel进行数据链接的精密排种器性能指标统计分析软件。研究得出该系统界面友好,与Excel数据链接方便,具有自动导入试验数据、保存和查找计算结果及比较分析试验结果的功能。此软件可大大地提高计算效率,保证数据处理的可靠性和计算结果的准确性。     

重力式计量包装机的设计与研究

介绍了定量包装机的结构、气缸选型以及料仓容积等参数的计算。该机配以PLC气动控制装置、嵌入式电脑核心的包装机控制仪,具有高精度、高速度及长期工作可靠性好等特点。它可以和自动取袋、封口机配合使用,根据不同物料的料性及工艺要求,进行自动称重包装,从而满足了国内粮食及其初深加工产品计量包装的性能指标要求,并广泛应用于粮食、化工等行业。     

万能通用精准播种机的研究与试验

通过对排种机理的研究，阐述了播种机两大系列产品的通用化问题。通过对锥盘式小麦精准播种机的研究、应用及改进，解决了以锥盘式精准排种器为基础、以“一组三行”播种单体为基型的播种机通用化问题。     

Neural network prediction of performance parameters of an inclined plate seed metering device and its reverse mapping for the determination of optimum design and operational parameters

Seed planting equipment with inclined plate seed metering devices is the most commonly used equipment for planting of peanut crop in India. For obtaining the high yield, it is very essential to drop the peanut seeds in rows maintaining accurate seed rate and seed spacing with minimum damage to seeds during metering. This mainly depends on forward speed of the planting equipment, rotary speed of the metering plate and area of cells on the plate. The relationship between these factors and the performance parameters viz., seed rate, seed spacing and percent seed damage can be established using regression analysis. But they may not be very accurate and may pose difficulty in the determination of inputs for a set of desired outputs (reverse mapping). Hence, an attempt has been made in this paper to develop the feed forward artificial neural network (ANN) models for the prediction of the performance parameters of an inclined plate seed metering device. The data were generated in the laboratory by conducting experiments on a sticky belt test stand provided with a seed metering device and an opto-electronic seed counter. The generated data was used to develop both statistical and neural network models. The performance of the developed models was compared among themselves for 4 randomly generated test cases. The results show that the ANN model predicted the performance parameters of the seed metering device better than the statistical models. In order to determine the optimum forward speed of the planting equipment, peripheral speed of the metering plate and the area of cells on the plate to obtain the recommended seed rate of 33.33 seeds/m², seed spacing of 100 mm and percent seed damage of 0.2% with 100% fill of the cells, a novel technique of reverse mapping using ANN model was followed. It was observed that the optimum forward speed of the planting equipment and optimum area of cells on the metering plate had good correlation with size of seed. Linear regression equations were developed to predict the optimum forward speed of the planting equipment and optimum area of cells on the metering plate using the size of seeds as independent parameter. The peripheral speed of the metering plate of 0.237 m/s was found to be optimum for the size of seeds in the range of 95.42-123.01 mm². However, the results need to be verified by conducting planting operation under actual field conditions.