本文選題：聯(lián)合收獲機(jī) + 脫粒系統(tǒng)��； 參考：《江蘇大學(xué)》2016年博士論文

【摘要】：聯(lián)合收獲機(jī)在田間收獲作業(yè)時(shí),田間作物密度、作物含水率、甚至地形的變化都會(huì)影響其喂入量的變化,而喂入量的變化會(huì)造成割臺(tái)螺旋輸送器、輸送槽和脫粒滾筒的轉(zhuǎn)速發(fā)生變化,其中脫粒滾筒的轉(zhuǎn)速變化又將直接影響脫粒滾筒的工作性能。因此,割臺(tái)螺旋輸送器、輸送槽、脫粒滾筒的轉(zhuǎn)速、前進(jìn)速度與喂入量、谷物收獲損失率之間就存在著某種關(guān)聯(lián)性。分析聯(lián)合收獲機(jī)多源作業(yè)信息之間的關(guān)聯(lián)性,開(kāi)展基于關(guān)聯(lián)規(guī)則聯(lián)合收獲機(jī)全論域作業(yè)速度自適應(yīng)控制系統(tǒng)研究,對(duì)探索聯(lián)合收獲機(jī)作業(yè)速度自適應(yīng)控制規(guī)律以及尋找新的智能控制算法,都具有重要的現(xiàn)實(shí)意義和科學(xué)研究?jī)r(jià)值。本文結(jié)合國(guó)家“863”計(jì)劃和江蘇省科技支撐計(jì)劃等項(xiàng)目,綜合運(yùn)用模型分析、關(guān)聯(lián)規(guī)則數(shù)據(jù)挖掘技術(shù)、動(dòng)力學(xué)分析與建模、計(jì)算機(jī)仿真、嵌入式技術(shù)等技術(shù)與理論,開(kāi)展基于關(guān)聯(lián)規(guī)則聯(lián)合收獲機(jī)全論域作業(yè)速度自適應(yīng)控制系統(tǒng)研究,主要工作包括:1、在聯(lián)合收獲機(jī)作業(yè)系統(tǒng)模型分析和作業(yè)參數(shù)關(guān)聯(lián)規(guī)則挖掘的基礎(chǔ)上,提取作業(yè)參數(shù)與喂入量、損失率之間的關(guān)聯(lián)規(guī)則,獲取各作業(yè)參數(shù)影響喂入量和損失率有價(jià)值的關(guān)聯(lián)知識(shí)。通過(guò)分析聯(lián)合收獲機(jī)作業(yè)系統(tǒng)各主要工作部件的數(shù)學(xué)模型可知,聯(lián)合收獲機(jī)主要作業(yè)參數(shù)(割臺(tái)螺旋輸送器轉(zhuǎn)速、輸送槽轉(zhuǎn)速、脫粒滾筒轉(zhuǎn)速、前進(jìn)速度)與喂入量、損失率之間存在著某種關(guān)聯(lián)性;依據(jù)關(guān)聯(lián)規(guī)則挖掘技術(shù),對(duì)聯(lián)合收獲機(jī)作業(yè)參數(shù)數(shù)據(jù)樣本進(jìn)行關(guān)聯(lián)規(guī)則數(shù)據(jù)挖掘,獲取脫粒滾筒轉(zhuǎn)速、割臺(tái)螺旋輸送器轉(zhuǎn)速、輸送槽轉(zhuǎn)速等作業(yè)參數(shù)對(duì)喂入量和損失率有影響的關(guān)聯(lián)規(guī)則知識(shí),并根據(jù)知識(shí)的重要性和置信度,采用歸一化的方法評(píng)估各作業(yè)參數(shù)與聯(lián)合收獲機(jī)的喂入量和損失率之間的關(guān)聯(lián)規(guī)則權(quán)重因子�？紤]到所得數(shù)據(jù)的不完整性,權(quán)衡各作業(yè)參數(shù)與喂入量、損失率之間的關(guān)聯(lián)程度,設(shè)置脫粒滾筒轉(zhuǎn)速、割臺(tái)螺旋輸送器轉(zhuǎn)速、輸送槽轉(zhuǎn)速參數(shù)的權(quán)值區(qū)間為[0.4 0.6]、[0.3 0.5]和[0 0.3]。2、建立了聯(lián)合收獲機(jī)脫粒系統(tǒng)動(dòng)力學(xué)模型,并以此為基礎(chǔ)構(gòu)建了作業(yè)速度普通控制系統(tǒng)仿真模型,再融合作業(yè)參數(shù)的關(guān)聯(lián)知識(shí)構(gòu)建了基于關(guān)聯(lián)規(guī)則作業(yè)速度控制模型。針對(duì)已有滾筒功耗模型沒(méi)有考慮其他工作部件的運(yùn)動(dòng)對(duì)滾筒轉(zhuǎn)速變化造成影響的這一問(wèn)題,以XG610型聯(lián)合收獲機(jī)為研究對(duì)象,通過(guò)運(yùn)動(dòng)機(jī)構(gòu)的動(dòng)力學(xué)分析,建立了脫粒系統(tǒng)動(dòng)力學(xué)理論模型;構(gòu)建了聯(lián)合收獲機(jī)作業(yè)速度普通控制模型,并進(jìn)行仿真分析。從普通控制模型的脫粒滾筒轉(zhuǎn)速、前進(jìn)速度仿真曲線變化趨勢(shì)可以看出,聯(lián)合收獲機(jī)在喂入量出現(xiàn)較大變化時(shí),控制系統(tǒng)能夠?qū)γ摿L筒轉(zhuǎn)速、前進(jìn)速度做出有效的調(diào)控,滾筒轉(zhuǎn)速變化沒(méi)有超出允許變化范圍,說(shuō)明建立脫粒系統(tǒng)動(dòng)力學(xué)模型是合理可行的;同時(shí)在普通控制模型基礎(chǔ)上,融合作業(yè)參數(shù)的關(guān)聯(lián)知識(shí)構(gòu)建了基于關(guān)聯(lián)規(guī)則作業(yè)速度控制模型,并與普通控制模型進(jìn)行仿真對(duì)比。對(duì)比結(jié)果顯示在總體收獲性能基本相同的情況下,基于關(guān)聯(lián)規(guī)則作業(yè)速度控制模型的整體控制性能要好于普通控制模型,前者前進(jìn)速度的最大相對(duì)變化幅度要比后者減小了1.50%,穩(wěn)態(tài)相對(duì)變化幅度比后者減小了0.70%,系統(tǒng)調(diào)整時(shí)間也由后者約16s縮短成約11s,系統(tǒng)整體穩(wěn)定性好于普通控制模型。3、建立了基于關(guān)聯(lián)規(guī)則聯(lián)合收獲機(jī)全論域作業(yè)速度自適應(yīng)控制模型,并與基于關(guān)聯(lián)規(guī)則的控制模型和普通控制模型進(jìn)行仿真對(duì)比。在基于關(guān)聯(lián)規(guī)則聯(lián)合收獲機(jī)作業(yè)速度控制模型的基礎(chǔ)上,從全論域角度出發(fā)內(nèi)建立了一種基于關(guān)聯(lián)規(guī)則作業(yè)速度自適應(yīng)控制仿真模型;設(shè)計(jì)了全論域可調(diào)因子模糊控制器,建立了可調(diào)因子模糊整定規(guī)則,并對(duì)三種控制模型進(jìn)行仿真對(duì)比。仿真顯示在喂入量增加約15%時(shí),基于關(guān)聯(lián)規(guī)則的全論域作業(yè)速度自適應(yīng)控制模型能夠滿足對(duì)作業(yè)速度的調(diào)控要求,脫粒滾筒轉(zhuǎn)速相對(duì)額定值最大相對(duì)變化幅度約為5.48%,穩(wěn)態(tài)時(shí)滾筒轉(zhuǎn)速相對(duì)變化幅度約為2.62%;前進(jìn)速度相對(duì)設(shè)定值最大相對(duì)變化幅度約為9.00%,穩(wěn)態(tài)時(shí)相對(duì)變化幅度約為7.80%;系統(tǒng)調(diào)整時(shí)間大約為8s。喂入量和單位損失率穩(wěn)態(tài)時(shí)大小分別為3.88kg/s和0.55%/(kg/s)。對(duì)比結(jié)果顯示,基于關(guān)聯(lián)規(guī)則聯(lián)合收獲機(jī)全論域作業(yè)速度自適應(yīng)控制模型不僅在控制性能方面優(yōu)于基于關(guān)聯(lián)規(guī)則的控制模型和普通控制模型,而且在總體收獲性能方面也好于基于關(guān)聯(lián)規(guī)則的控制模型和普通控制模型。4、對(duì)聯(lián)合收獲機(jī)作業(yè)速度控制的硬件系統(tǒng)組成和軟件系統(tǒng)開(kāi)發(fā)進(jìn)行研究,并對(duì)控制系統(tǒng)進(jìn)行室內(nèi)測(cè)試。硬件系統(tǒng)主要由arm9系統(tǒng)、轉(zhuǎn)速信號(hào)采集模塊、液晶觸摸顯示屏和聯(lián)合收獲機(jī)作業(yè)速度自動(dòng)調(diào)控裝置等部分組成,同時(shí)系統(tǒng)預(yù)留了視頻監(jiān)測(cè)模塊和gps信號(hào)采集模塊的接口;開(kāi)發(fā)外接硬件設(shè)備驅(qū)動(dòng)程序和作業(yè)速度控制系統(tǒng)應(yīng)用軟件,應(yīng)用軟件共分為五個(gè)部分:系統(tǒng)主界面、參數(shù)設(shè)定界面、作業(yè)速度監(jiān)測(cè)與智能控制界面、視頻監(jiān)測(cè)界面和gps定位信息監(jiān)測(cè)界面。在聯(lián)合收獲機(jī)室內(nèi)模擬調(diào)速裝置上對(duì)系統(tǒng)進(jìn)行了測(cè)試。測(cè)試結(jié)果顯示,系統(tǒng)對(duì)監(jiān)測(cè)的數(shù)據(jù)實(shí)時(shí)穩(wěn)定,當(dāng)分別采用普通控制算法、基于關(guān)聯(lián)規(guī)則控制算法和基于關(guān)聯(lián)規(guī)則全論域自適應(yīng)控制算法對(duì)步進(jìn)電機(jī)的控制符合聯(lián)合收獲機(jī)前進(jìn)速度的調(diào)節(jié)要求。5、進(jìn)行作業(yè)速度控制系統(tǒng)機(jī)載調(diào)試,并針對(duì)三種控制模型的控制算法開(kāi)展田間收割試驗(yàn)與對(duì)比驗(yàn)證。機(jī)載調(diào)試主要開(kāi)展各工作部件轉(zhuǎn)速的標(biāo)定、前進(jìn)速度的標(biāo)定以及自動(dòng)控制作業(yè)測(cè)試等工作。分別采用普通控制算法、基于關(guān)聯(lián)規(guī)則的控制算法和基于關(guān)聯(lián)規(guī)則全論域自適應(yīng)控制算法進(jìn)行水稻收割試驗(yàn),并進(jìn)行試驗(yàn)數(shù)據(jù)分析和對(duì)比。從三種控制算法的脫粒滾筒轉(zhuǎn)速和前進(jìn)速度試驗(yàn)數(shù)據(jù)曲線總體變化趨勢(shì)上可以看出,滾筒轉(zhuǎn)速與前進(jìn)速度的變化與仿真分析結(jié)果相符合,三種控制算法的脫粒滾筒轉(zhuǎn)速最大變化幅度沒(méi)有超出額定值7%的允許變化范圍,這也進(jìn)一步驗(yàn)證了所建立的脫粒系統(tǒng)動(dòng)力學(xué)模型是合理可行的。同時(shí)對(duì)比結(jié)果顯示,在控制性能方面,基于關(guān)聯(lián)規(guī)則全論域自適應(yīng)控制算法獲得的脫粒滾筒轉(zhuǎn)速穩(wěn)態(tài)時(shí)平均變化幅度為2.97%、前進(jìn)速度最大變化幅度9.00%、到達(dá)基本穩(wěn)定狀態(tài)所需時(shí)間約7s,均優(yōu)于普通控制算法和基于關(guān)聯(lián)規(guī)則控制算法獲得的控制性能數(shù)據(jù);在收獲性能方面,基于關(guān)聯(lián)規(guī)則的全論域自適應(yīng)控制算法的聯(lián)合收獲機(jī)平均喂入量比基于關(guān)聯(lián)規(guī)則的控制算法和普通控制算法下的平均喂入量要略小,但該算法下的平均損失率要比后兩種控制算法下的平均損失率分別要低0.29%和0.22%,單位平均損失率要比后兩種控制算法分別要低0.06%/(kg/s)和0.05%/(kg/s),損失率降低幅度較大。因此,基于關(guān)聯(lián)規(guī)則全論域作業(yè)速度自適應(yīng)控制系統(tǒng)不僅在控制性能方面優(yōu)于后兩種控制系統(tǒng),而且在總體收獲性能方面也好于后兩種控制系統(tǒng)。
[Abstract]:When the harvester is harvested in the field, the field crop density, the water content of the crop, and even the change of the terrain will affect the change of the feeding amount, and the change of feed quantity will cause the screw conveyor of the cutting platform, the speed of the conveying slot and the threshing roller change, and the change of the speed of the threshing barrel will directly affect the work of the threshing roller. Therefore, there is some correlation between the rotating speed of the screw conveyor, the conveying tank and the threshing roller, the speed of advance and the feed rate, the loss rate of the grain harvest, and the correlation between the multi source work information of the combined harvester and the study of the adaptive control system of the full domain operation speed based on the association rules and the joint harvesting machine. It is of great practical significance and scientific research value to explore the adaptive control law of the working speed of the joint harvester and to find a new intelligent control algorithm. This paper combines the national "863" plan and the Jiangsu science and technology support program, and comprehensively uses the model analysis, the closed rule data mining technology, the dynamic analysis and modeling. On the basis of computer simulation, embedded technology and other technologies and theories, the research on adaptive control system of full domain operation speed based on association rules is carried out. The main work includes: 1. On the basis of the model analysis of the joint harvester operating system and the mining of the association rules of the operating parameters, the extraction of the operation parameters and the feed rate and the loss rate are extracted. Association rules are used to obtain relevant knowledge about the value of feed volume and loss rate. Through the analysis of the mathematical models of the main working parts of the combined harvester, the main operating parameters of the combined harvester (rotating speed of the screw conveyor, the speed of the conveyor, the speed of the threshing roller, the speed of advance) and the loss of the feed are found. According to the association rule mining technology, the association rule data mining is carried out on the data samples of the joint harvester operation parameter data to obtain the knowledge of the association rules which have influence on the feeding quantity and loss rate, and the knowledge is weighed according to the knowledge, and the speed of the threshing roller, the speed of the screw conveyor and the speed of the conveyor, and so on. To evaluate the correlation rule weight factor between the operating parameters and the feed intake and loss rate of the combined harvester. Considering the incompleteness of the data, the degree of association between the operating parameters and the feed volume and the loss rate is weighed, and the rotational speed of the threshing roller, the speed of the screw conveyor of the cutting platform, and the transmission of the screw conveyor are taken into account. The weight range of the rotating speed parameters of the grooves is [0.4 0.6], [0.3 0.5] and [0 0.3].2. The dynamic model of the threshing system of the joint harvester is set up. On the basis of this, the simulation model of the operation speed ordinary control system is built. Then the association knowledge of operation parameters is used to construct the operation speed control model based on the association rules. The consumption model does not take into account the problem that the movement of other working components affects the change of the rotational speed of the drum. Taking the XG610 type combined harvester as the research object, the dynamic theoretical model of the threshing system is established through the dynamic analysis of the motion mechanism, and the general control model of the combined harvester is constructed, and the simulation analysis is carried out. It can be seen that the control system can effectively control the speed and speed of the threshing drum when the feed volume of the combined harvester changes greatly, and the change of the rotational speed of the drum does not exceed the allowable range of change, indicating the establishment of the dynamic model of the threshing system. It is reasonable and feasible. At the same time, based on the common control model, the operation speed control model based on association rules is constructed and compared with the common control model. The comparison results show that the speed control model based on the association rule operation speed control model is the same as the overall harvest performance is basically the same. The body control performance is better than the ordinary control model, the maximum relative change range of the former speed is 1.50% less than the latter, the relative change amplitude of the steady state is 0.70% less than the latter, and the adjustment time of the system is shortened by about 16S by about 11S, and the overall stability of the system is better than the universal control model.3, and the association rules are set up based on the association rules. The adaptive control model of the machine full domain operation speed is simulated and compared with the control model based on the association rules and the common control model. Based on the association rule combined with the harvest speed control model of the harvester, an adaptive control simulation model based on the operation speed of association rules is established from the point of view of the whole domain. The whole domain adjustable factor fuzzy controller is designed, the adjustable factor fuzzy setting rule is established, and the simulation comparison of the three control models is carried out. The simulation shows that when the feeding amount is increased by about 15%, the adaptive control model of the whole domain operation speed adaptive control model based on the association rules can be full of the operation speed regulation and the threshing roller speed. The relative variation amplitude of the relative nominal value is about 5.48%, the relative change amplitude of the roller speed is about 2.62% in the steady state, the maximum relative change amplitude of the forward velocity relative to the set value is about 9%, the relative change amplitude is about 7.80% in the steady state, and the system adjustment time is about 3.88kg/s and 0.5, respectively, when the 8s. feed and unit loss rate are steady. 5%/ (kg/s). The comparison results show that the adaptive control model based on the association rule combined harvester total domain job speed adaptive control is not only better than the control model and ordinary control model based on association rules in control performance, but also better than the control model based on association rules and the common control model.4 in the overall harvest performance. The hardware system and software system development of the harvester operating speed control are studied and the control system is tested indoors. The hardware system is mainly composed of ARM9 system, speed signal acquisition module, liquid crystal touch screen and joint harvester operation speed automatic control device and so on. Meanwhile, the system is reserved for video monitoring. The interface of module and GPS signal acquisition module; development of external hardware device driver and operation speed control system application software. The application software is divided into five parts: system main interface, parameter setting interface, operation speed monitoring and intelligent control interface, video monitoring interface and GPS positioning information monitoring interface. The test results show that the system is stable to the monitoring data in real time. When the common control algorithm is adopted, the control of the stepping motor based on the association rule control algorithm and the full domain adaptive control algorithm based on the association rules conforms to the adjustment requirement of the forward speed of the combined harvester.5. The operation speed control system is debugged, and the field harvest test and contrast verification are carried out against the control algorithms of three control models. The airborne debug mainly carries out the calibration of the rotational speed of the working parts, the calibration of the forward speed and the automatic control operation test. The general control algorithm and the control algorithm based on the association rules are adopted respectively. The rice harvesting experiment based on the full domain adaptive control algorithm based on the association rules is carried out, and the experimental data are analyzed and compared. The change trend of the speed and forward speed of the three control algorithms can be seen that the change of the roller speed and the forward speed conforms to the results of the simulation analysis, and the three kinds of control are controlled. The maximum change range of the rotational speed of the threshing cylinder is not beyond the allowable range of the rated value of 7%, which further proves that the dynamic model of the threshing system is reasonable and feasible. At the same time, the comparison results show that the rotational speed of the threshing drum is obtained on the basis of the correlation rule full domain adaptive control algorithm in the control performance. The average change amplitude of the steady state is 2.97% and the maximum change range of the forward speed is 9%. The time required to reach the basic stable state is about 7S, which is better than the control performance data obtained by the common control algorithm and the association rule control algorithm. The feeding amount is slightly smaller than that of the control algorithm based on the association rules and the average control algorithm under the common control algorithm, but the average loss rate under this algorithm is 0.29% and 0.22% lower than the average loss rate under the two control algorithms. The unit average loss rate is lower 0.06%/ (kg/s) and 0.05%/ (kg/s) than the latter two control algorithms, and the loss rate is lower than the latter. The rate of rate reduction is larger. Therefore, the adaptive control system based on the association rule full domain operation speed adaptive control is superior to the latter two control systems, and the overall harvest performance is better than the latter two control systems.
【學(xué)位授予單位】：江蘇大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：S225

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