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

【摘要】：聯合收獲機在田間收獲作業(yè)時,田間作物密度、作物含水率、甚至地形的變化都會影響其喂入量的變化,而喂入量的變化會造成割臺螺旋輸送器、輸送槽和脫粒滾筒的轉速發(fā)生變化,其中脫粒滾筒的轉速變化又將直接影響脫粒滾筒的工作性能。因此,割臺螺旋輸送器、輸送槽、脫粒滾筒的轉速、前進速度與喂入量、谷物收獲損失率之間就存在著某種關聯性。分析聯合收獲機多源作業(yè)信息之間的關聯性,開展基于關聯規(guī)則聯合收獲機全論域作業(yè)速度自適應控制系統(tǒng)研究,對探索聯合收獲機作業(yè)速度自適應控制規(guī)律以及尋找新的智能控制算法,都具有重要的現實意義和科學研究價值。本文結合國家“863”計劃和江蘇省科技支撐計劃等項目,綜合運用模型分析、關聯規(guī)則數據挖掘技術、動力學分析與建模、計算機仿真、嵌入式技術等技術與理論,開展基于關聯規(guī)則聯合收獲機全論域作業(yè)速度自適應控制系統(tǒng)研究,主要工作包括:1、在聯合收獲機作業(yè)系統(tǒng)模型分析和作業(yè)參數關聯規(guī)則挖掘的基礎上,提取作業(yè)參數與喂入量、損失率之間的關聯規(guī)則,獲取各作業(yè)參數影響喂入量和損失率有價值的關聯知識。通過分析聯合收獲機作業(yè)系統(tǒng)各主要工作部件的數學模型可知,聯合收獲機主要作業(yè)參數(割臺螺旋輸送器轉速、輸送槽轉速、脫粒滾筒轉速、前進速度)與喂入量、損失率之間存在著某種關聯性;依據關聯規(guī)則挖掘技術,對聯合收獲機作業(yè)參數數據樣本進行關聯規(guī)則數據挖掘,獲取脫粒滾筒轉速、割臺螺旋輸送器轉速、輸送槽轉速等作業(yè)參數對喂入量和損失率有影響的關聯規(guī)則知識,并根據知識的重要性和置信度,采用歸一化的方法評估各作業(yè)參數與聯合收獲機的喂入量和損失率之間的關聯規(guī)則權重因子。考慮到所得數據的不完整性,權衡各作業(yè)參數與喂入量、損失率之間的關聯程度,設置脫粒滾筒轉速、割臺螺旋輸送器轉速、輸送槽轉速參數的權值區(qū)間為[0.4 0.6]、[0.3 0.5]和[0 0.3]。2、建立了聯合收獲機脫粒系統(tǒng)動力學模型,并以此為基礎構建了作業(yè)速度普通控制系統(tǒng)仿真模型,再融合作業(yè)參數的關聯知識構建了基于關聯規(guī)則作業(yè)速度控制模型。針對已有滾筒功耗模型沒有考慮其他工作部件的運動對滾筒轉速變化造成影響的這一問題,以XG610型聯合收獲機為研究對象,通過運動機構的動力學分析,建立了脫粒系統(tǒng)動力學理論模型;構建了聯合收獲機作業(yè)速度普通控制模型,并進行仿真分析。從普通控制模型的脫粒滾筒轉速、前進速度仿真曲線變化趨勢可以看出,聯合收獲機在喂入量出現較大變化時,控制系統(tǒng)能夠對脫粒滾筒轉速、前進速度做出有效的調控,滾筒轉速變化沒有超出允許變化范圍,說明建立脫粒系統(tǒng)動力學模型是合理可行的;同時在普通控制模型基礎上,融合作業(yè)參數的關聯知識構建了基于關聯規(guī)則作業(yè)速度控制模型,并與普通控制模型進行仿真對比。對比結果顯示在總體收獲性能基本相同的情況下,基于關聯規(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,前者前進速度的最大相對變化幅度要比后者減小了1.50%,穩(wěn)態(tài)相對變化幅度比后者減小了0.70%,系統(tǒng)調整時間也由后者約16s縮短成約11s,系統(tǒng)整體穩(wěn)定性好于普通控制模型。3、建立了基于關聯規(guī)則聯合收獲機全論域作業(yè)速度自適應控制模型,并與基于關聯規(guī)則的控制模型和普通控制模型進行仿真對比。在基于關聯規(guī)則聯合收獲機作業(yè)速度控制模型的基礎上,從全論域角度出發(fā)內建立了一種基于關聯規(guī)則作業(yè)速度自適應控制仿真模型;設計了全論域可調因子模糊控制器,建立了可調因子模糊整定規(guī)則,并對三種控制模型進行仿真對比。仿真顯示在喂入量增加約15%時,基于關聯規(guī)則的全論域作業(yè)速度自適應控制模型能夠滿足對作業(yè)速度的調控要求,脫粒滾筒轉速相對額定值最大相對變化幅度約為5.48%,穩(wěn)態(tài)時滾筒轉速相對變化幅度約為2.62%;前進速度相對設定值最大相對變化幅度約為9.00%,穩(wěn)態(tài)時相對變化幅度約為7.80%;系統(tǒng)調整時間大約為8s。喂入量和單位損失率穩(wěn)態(tài)時大小分別為3.88kg/s和0.55%/(kg/s)。對比結果顯示,基于關聯規(guī)則聯合收獲機全論域作業(yè)速度自適應控制模型不僅在控制性能方面優(yōu)于基于關聯規(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聯規(guī)則的控制模型和普通控制模型。4、對聯合收獲機作業(yè)速度控制的硬件系統(tǒng)組成和軟件系統(tǒng)開發(fā)進行研究,并對控制系統(tǒng)進行室內測試。硬件系統(tǒng)主要由arm9系統(tǒng)、轉速信號采集模塊、液晶觸摸顯示屏和聯合收獲機作業(yè)速度自動調控裝置等部分組成,同時系統(tǒng)預留了視頻監(jiān)測模塊和gps信號采集模塊的接口;開發(fā)外接硬件設備驅動程序和作業(yè)速度控制系統(tǒng)應用軟件,應用軟件共分為五個部分:系統(tǒng)主界面、參數設定界面、作業(yè)速度監(jiān)測與智能控制界面、視頻監(jiān)測界面和gps定位信息監(jiān)測界面。在聯合收獲機室內模擬調速裝置上對系統(tǒng)進行了測試。測試結果顯示,系統(tǒng)對監(jiān)測的數據實時穩(wěn)定,當分別采用普通控制算法、基于關聯規(guī)則控制算法和基于關聯規(guī)則全論域自適應控制算法對步進電機的控制符合聯合收獲機前進速度的調節(jié)要求。5、進行作業(yè)速度控制系統(tǒng)機載調試,并針對三種控制模型的控制算法開展田間收割試驗與對比驗證。機載調試主要開展各工作部件轉速的標定、前進速度的標定以及自動控制作業(yè)測試等工作。分別采用普通控制算法、基于關聯規(guī)則的控制算法和基于關聯規(guī)則全論域自適應控制算法進行水稻收割試驗,并進行試驗數據分析和對比。從三種控制算法的脫粒滾筒轉速和前進速度試驗數據曲線總體變化趨勢上可以看出,滾筒轉速與前進速度的變化與仿真分析結果相符合,三種控制算法的脫粒滾筒轉速最大變化幅度沒有超出額定值7%的允許變化范圍,這也進一步驗證了所建立的脫粒系統(tǒng)動力學模型是合理可行的。同時對比結果顯示,在控制性能方面,基于關聯規(guī)則全論域自適應控制算法獲得的脫粒滾筒轉速穩(wěn)態(tài)時平均變化幅度為2.97%、前進速度最大變化幅度9.00%、到達基本穩(wěn)定狀態(tài)所需時間約7s,均優(yōu)于普通控制算法和基于關聯規(guī)則控制算法獲得的控制性能數據;在收獲性能方面,基于關聯規(guī)則的全論域自適應控制算法的聯合收獲機平均喂入量比基于關聯規(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,基于關聯規(guī)則全論域作業(yè)速度自適應控制系統(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.
【學位授予單位】：江蘇大學
【學位級別】：博士
【學位授予年份】：2016
【分類號】：S225

【相似文獻】

相關期刊論文 前10條

1 趙金山,閆和平;河北省聯合收獲機市場質量普查結果和分析[J];河北農機;2000年02期

2 王曉樸,崔振錄;降低稻麥聯合收獲機籽粒破碎率的有效措施[J];農機維修;2000年05期

3 鄭長安;聯合收獲機的正確使用[J];農業(yè)機械化與電氣化;2000年01期

4 王豐勇;乳山市農機局改造小麥聯合收獲機——一機兩用跨區(qū)收獲水稻[J];山東農機化;2000年11期

5 胡偉;我國聯合收獲機發(fā)展形勢分析[J];農機市場;2001年07期

6 胡偉;;我國收獲機械的六大關注點[J];農業(yè)機械;2002年10期

7 高民;小麥聯合收獲機的應用[J];河南科技;2002年06期

8 謝楊青;降低稻麥聯合收獲機籽料破碎率的有效措施[J];農機具之友;2002年02期

9 武志宏;聯合收獲機的正確保管[J];農機安全監(jiān)理;2002年Z1期

10 永泰;聯合收獲機操作中的10個問題[J];農機安全監(jiān)理;2002年Z1期

相關會議論文 前9條

1 張軍;趙德安;秦云;;聯合收獲機脫粒滾筒轉速的魯棒控制[A];中國自動化學會控制理論專業(yè)委員會A卷[C];2011年

2 魏宵;謝方平;葉強;孫松林;;水稻半喂入聯合收獲機堵塞成因及其調控技術分析[A];中國農業(yè)工程學會2011年學術年會論文集[C];2011年

3 張?zhí)祢?;水稻聯合收獲機性能分析與選型[A];第十屆沈陽科學學術年會論文集（農業(yè)科學與醫(yī)藥科學分冊）[C];2013年

4 閻楚良;楊方飛;;基于實例推理技術在聯合收獲機數字化設計開發(fā)中的應用研究[A];走中國特色農業(yè)機械化道路——中國農業(yè)機械學會2008年學術年會論文集（下冊）[C];2008年

5 介戰(zhàn);;聯合收獲機損失率測試研究展望[A];2007年中國農業(yè)工程學會學術年會論文摘要集[C];2007年

6 巫尚榮;楊堅;梁兆新;覃家松;;聯合收割機清糧機構的仿真優(yōu)化研究[A];中國農業(yè)機械學會成立40周年慶典暨2003年學術年會論文集[C];2003年

7 張得儉;寇明杰;張娟娟;;4UL1500馬鈴薯聯合收獲機功率消耗的分析與研究[A];2009海峽兩岸機械科技論壇論文集[C];2009年

8 張得儉;寇明杰;張娟娟;;4UL1500馬鈴薯聯合收獲機功率消耗的分析與研究[A];十三省區(qū)市機械工程學會第五屆科技論壇論文集[C];2009年

9 周俊;劉成良;;沖量式谷物智能測產系統(tǒng)設計[A];農業(yè)機械化與新農村建設——中國農業(yè)機械學會2006年學術年會論文集（上冊）[C];2006年

相關重要報紙文章 前10條

1 胡偉 張寶苓 劉玉樂;解析收獲機械六大熱門話題[N];中國機電日報;2002年

2 王大慶;收獲機技術發(fā)展研討會將辦[N];中國工業(yè)報;2003年

3 荊叢林 張清;怎樣選購小麥聯合收獲機[N];山東科技報;2006年

4 子玉;小麥聯合收獲機使用注意事項[N];農民日報;2010年

5 王青華;花生聯合收獲機操作技術要點(上)[N];中國農機化導報;2013年

6 王青華;花生聯合收獲機操作技術要點(下)[N];中國農機化導報;2013年

7 李憲義;聯合收獲機田間操作與調整[N];中國農機化導報;2014年

8 農友;新小麥聯合收獲機開割前勿忘磨合[N];陜西科技報;2008年

9 本報記者 王敏;“沭河”花生聯合收獲機性能更優(yōu)越[N];河北科技報;2014年

10 陸秉宏;專家研制出新型甜菜聯合收獲機[N];農民日報;2012年

相關博士學位論文 前4條

1 寧小波;基于關聯規(guī)則聯合收獲機全論域作業(yè)速度自適應控制系統(tǒng)[D];江蘇大學;2016年

2 胡志超;半喂入花生聯合收獲機關鍵技術研究[D];南京農業(yè)大學;2011年

3 楊然兵;4HQL-2型花生聯合收獲機主要裝置的設計與試驗研究[D];沈陽農業(yè)大學;2009年

4 唐忠;切縱流結構谷物脫粒分離理論與試驗研究[D];江蘇大學;2013年

相關碩士學位論文 前10條

1 段震華;檸條聯合收獲機輸送切碎機構設計[D];山西農業(yè)大學;2015年

2 姜彥武;4U-1600型馬鈴薯聯合收獲機的設計與研究[D];甘肅農業(yè)大學;2016年

3 陳洋;斜置切縱流聯合收獲機脫粒分離裝置參數優(yōu)化與試驗[D];江蘇大學;2016年

4 陳勁松;履帶式聯合收獲機差逆轉向系統(tǒng)動態(tài)模擬及試驗[D];江蘇大學;2016年

5 王亞丁;履帶式聯合收獲機駕駛臺振動分析與結構優(yōu)化[D];江蘇大學;2016年

6 王兵;John Deere JL 1075聯合收獲機低割裝置的設計[D];南京農業(yè)大學;2004年

7 廖曉蓮;水稻聯合收獲機跨區(qū)作業(yè)研究[D];湖南農業(yè)大學;2007年

8 成仲利;小麥聯合收獲機氣力清倉系統(tǒng)的研究與分析[D];山東理工大學;2009年

9 李偉;聯合收獲機產量分布信息獲取技術研究[D];中國農業(yè)機械化科學研究院;2012年

10 張建;4M-2型馬鈴薯聯合收獲機優(yōu)化設計與仿真[D];甘肅農業(yè)大學;2008年

，

本文編號：2105275