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基于頂芽智能識別的棉花化學(xué)打頂系統(tǒng)研究
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財政部和農(nóng)業(yè)農(nóng)村部:國家現(xiàn)代農(nóng)業(yè)產(chǎn)業(yè)技術(shù)體系項目(CARS-15-22)、山東省引進(jìn)頂尖人才“一事一議”專項(魯政辦字〔2018〕27號)和教育部、農(nóng)業(yè)農(nóng)村部、中國科協(xié)“山東無棣棉花科技小院”建設(shè)項目


Research on Cotton Chemical Topping System Based on Apical Bud Intelligent Recognition
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    摘要:

    設(shè)計了基于頂芽智能識別的棉花化學(xué)打頂系統(tǒng),為實現(xiàn)精準(zhǔn)作業(yè),合理高效使用棉花化學(xué)打頂藥劑,以減少因化學(xué)打頂劑的過度使用造成的環(huán)境污染。該系統(tǒng)主要由棉花頂芽識別系統(tǒng)、控制系統(tǒng)和噴施系統(tǒng)組成。采用YOLO v5s算法構(gòu)建棉花頂芽識別模型。控制系統(tǒng)采用STM32F407單片機(jī),負(fù)責(zé)接收識別系統(tǒng)的信號,并對各個棉花打頂劑管道進(jìn)行控制。同時,顯示界面能夠?qū)崟r顯示機(jī)具行駛速度、藥液流量、打頂劑液位等參數(shù)。試驗結(jié)果表明,在田間全天光照試驗中,上午和下午時間段識別效果最優(yōu);在速度0.4m/s下,平均識別率約為94%;信號發(fā)送區(qū)間為100mm時,成功向下位機(jī)發(fā)送信號的成功率達(dá)到92%;田間對靶噴施試驗表明,有效噴施率為94%,滿足作業(yè)要求。

    Abstract:

    A cotton chemical topping system based on top bud intelligent recognition was designed to achieve precise operation, rational and efficient use of cotton chemical topping agents, and reduce environmental pollution caused by excessive use of chemical topping agents. The system mainly consisted of cotton top bud recognition system, control system, and spraying system. A cotton top bud recognition model was constructed by using the YOLO v5s algorithm. The control system adopted STM32F407 microcontroller, which was responsible for receiving signals from the recognition system and controlling various cotton topping agent pipelines. At the same time, the display interface can display real-time parameters such as the driving speed of the equipment, the flow rate of the medicine, and the liquid level of the topping agent. The experimental results showed that in the field all day light experiment, the morning and afternoon time periods had the best recognition performance. At a speed of 0.4m/s, the average recognition rate was about 94%. When the signal transmission interval was 100mm, the success rate of successfully sending signals to the lower computer reached 92%. The field target spraying experiment showed that the effective spraying rate was 94%, which met the spraying requirements.

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韓鑫,韓金鴿,陳允琳,蘭玉彬,李建坤,崔立華.基于頂芽智能識別的棉花化學(xué)打頂系統(tǒng)研究[J].農(nóng)業(yè)機(jī)械學(xué)報,2024,55(3):145-152. HAN Xin, HAN Jin'ge, CHEN Yunlin, LAN Yubin, LI Jiankun, CUI Lihua. Research on Cotton Chemical Topping System Based on Apical Bud Intelligent Recognition[J]. Transactions of the Chinese Society for Agricultural Machinery,2024,55(3):145-152.

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  • 收稿日期:2023-08-09
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  • 在線發(fā)布日期: 2023-09-03
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