【作者】 王征；

【导师】 宋月鹏；

【作者基本信息】 山东农业大学 ， 农业电气化与自动化， 2024， 博士

【摘要】 饲草生产在畜牧业中占据重要地位,目前我国饲草料作物的机械化收获已逐渐普及,但国产饲草收获机的自动化作业可靠性与国外相比差距明显,高端饲草收获机大多靠国外引进,市场占有率较低。自动化程度及作业功效(单位作业能耗)低是导致收获机作业可靠性差的重要因素,而作业负荷反馈控制系统及其算法是解决该问题的关键核心技术,因此,本文开展了以提高饲草收获机作业功效及可靠性为目标,基于切碎负荷在线检测及其与切刀负荷阈值的比较结果,对关键作业部件的负荷检测、控制及其算法优化的研究,并进行了验证实验,研究结果为我国突破高端饲草收获机研发,促进解决制约畜牧业快速发展的卡脖子难题提供理论及数据支撑。本文主要研究内容如下:(1)利用研制的饲草切碎调制机,建立了发动机、喂入、切碎等饲草收获机关键部件的作业动力学模型,构建了饲草收获的数学模型;在Simuilink软件环境下设计了收获机仿真模型,对关键部件的作业稳态特性、扰动瞬态响应进行研究。结果表明,收获机关键部件的内部参数和外部扰动对其工作状态有显著影响,作业系统是一种阶次较高的典型大惯性和纯延时系统,存在较强的非线性与时变性。(2)基于液体减震基本原理和切碎传动带压力检测初始值、滑动-效率关系,建立收获机最优作业效能的传动带压力负荷检测模型,并设计了作业负荷检测系统;以切碎玉米秸秆为例,在饲草切碎调制机上对传动带作业压力负荷实时检测。结果表明,所研发的检测系统准确率较高,具有良好的实时性、经济性、可靠性等特点。(3)基于降低外部扰动对切碎作业的影响,提出了通过串级控制主回路调整切碎及喂入负荷,控制副回路调整发动机转速,采用模糊技术实现负荷控制自适应;采用DGPC与MPC预测技术,解决收获机的非线性、大惯性、纯延时,抑制外部扰动等问题;负荷-转速串级模糊非线性预测控制模型中,通过引入转速副回路,提高系统工作频次及强化系统内部参数等方法,提升系统对外部扰动的控制效果。多种工况条件下的仿真及试验表明,构建的负荷反馈控制系统具有一定自适应能力和较好的控制效果,实现了饲草收获机喂入、切碎作业负荷的在线检测与反馈控制。(4)为进一步提升作业功效及控制的可靠性,基于最小能量原理、模糊预测理论、动力输出外特性及作业功效测定阈值,提出了一种饲草收获负荷分割优化控制算法。以玉米秸秆为切碎饲草作物,计算机仿真及收获机验证结果表明,在恒功率输出的条件下,该优化算法可使饲草收获机关键部件作业的功效负荷阈值(1207.8 N)获得提高。(5)饲草收获机关键部件负荷控制系统及其优化算法,试验结果表明,该作业负荷检测与反馈控制系统及其优化算法具有较高的可靠性,收获机的喂入、切碎等关键作业控制过程运行稳定。构建的功效阈值负荷分割优化控制算法,与传统算法相比,同等试验条件下,关键部件作业控制稳态精度提高了29.81%,响应时间提高了24.69%,切碎功效负荷阈值提高了57.30%,保证质量下切碎效率提高了1.52倍,单位能耗节约7.25%。该优化控制算法对饲草收获机作业参数变化适应及时滞控制能力更强,动力供给及分配更为合理,可以显著解决饲草收获机作业过程中的堵转、关键部件作业动力分配不当问题,明显减小单位作业能耗。研究结果对其他机械负荷反馈控制系统及其算法优化的研究和应用具有一定的借鉴价值。更多还原

【Abstract】 Forage production plays an important role in animal husbandry.Currently,the mechanized harvesting of forage crops in China has gradually become popular.However,the reliability of automated operation of domestic forage harvesters lags behind that of foreign countries.Most high-end forage harvesters rely on foreign imports,resulting in a low market share.The low level of automation and operational efficiency(unit energy consumption)are important factors that lead to poor reliability of harvester operations,and the feedback control system and its algorithm for operational load are the key core technologies to solve this problem.Therefore,this article aims to improve the operational efficiency and reliability of forage harvesters.Based on the online detection of chopping load and the comparison results with the cutting blade load threshold,the study focuses on the load detection,control,and algorithm optimization of key operational components,and conducts verification experiments.The research results provide theoretical and data support for China to break through the development of high-end forage harvesters and promote the resolution of the bottleneck problem that restricts the rapid development of animal husbandry.The main research contents of this paper are as follows:Firstly,the dynamic models of key components of forage harvester,such as engine,feeding and shredding,were established,and the mathematical model of forage harvester was established.The simulation model of harvester was designed under Simuilink software,and the steady-state characteristics and disturbance transient response of key components were studied.The results show that the internal parameters and external disturbances of the key components of the harvester have significant effects on its working state.The operating system is a typical large-inertia and pure delay system of higher order,with strong nonlinearity and time variability.Secondly,based on the basic principle of liquid shock absorption,the initial value of pressure detection and the slip-efficiency relationship of the chopped transmission belt,the detection model of the optimal working efficiency of the harvester’s transmission belt pressure load is established,and the working load detection system is designed.Taking corn straw shredding as an example,the pressure load of the transmission belt was measured in real time on the forage shredding machine.The results show that the developed detection system has high accuracy,good real-time performance,economy and reliability.Thirdly,in order to reduce the influence of external disturbance on the shredding operation,it is proposed to adjust the shredding and feeding load by controlling the main circuit and adjusting the engine speed by controlling the secondary circuit.DGPC and MPC prediction techniques are used to solve the problems of non-linearity,large inertia,pure delay and external disturbance suppression.In the load-speed cascade fuzzy nonlinear predictive control model,the speed sub-loop is introduced,the operating frequency of the system is increased and the internal parameters of the system are strengthened to improve the control effect of the system to the external disturbance.The simulation and test under various working conditions show that the constructed load feedback control system has certain adaptive ability and good control effect,and realizes the online detection and feedback control of feed and cut operation load of forage harvester.Fourthly,in order to improve operation efficiency and control reliability,an optimized control algorithm for forage harvest load segmentation was proposed based on minimum energy principle,fuzzy prediction theory,power output characteristics and operation efficiency measurement threshold.Taking corn stalk as forage crop,computer simulation and harvester verification results show that under the condition of constant power output,the optimization algorithm can improve the efficiency load threshold(1207.8N)of key components of the harvester.Fifthly,the load control system of key components of forage harvester and its optimization algorithm are proved to be highly reliable by the test results,and the key operation control processes such as feeding and shredding run stably.Compared with the traditional algorithm,under the same test conditions,the steady state precision of key component operation control is improved by 29.81%,the response time is increased by 24.69%,the shredding power load threshold is increased by 57.30%,the shredding efficiency is increased by 1.52 times under guaranteed quality,and the unit energy consumption is saved by 7.25%.The optimized control algorithm has stronger adaptability to the operation parameter changes of the forage harvester and more reasonable power supply and distribution,which can significantly solve the problems of gridlock and improper power distribution of key components during the operation of the forage harvester,and significantly reduce the unit operation energy consumption.The results can be used for reference in the research and application of other mechanical load feedback control systems and their algorithm optimization.更多还原