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基于機器視覺的乘用式智能采茶機設計與試驗
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“十二五”國家科技支撐計劃項目(2014BAD06B06)


Design and Experiment of Intelligentized Tea-plucking Machine for Human Riding Based on Machine Vision
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    摘要:

    針對目前乘用式采茶機作業(yè)時對采摘面的茶芽不能識別大小、老嫩茶葉一刀切下的弊端,設計了一種基于機器視覺的乘用式采茶機,提出了嫩茶自動識別與采茶機割刀的自動調平調高控制方法。通過對采茶機割臺的位置伺服和水平度伺服控制,使得割刀面與茶隴蓬面有一個較好吻合,并能將割臺與大地水平面保持一致;為了實現更為精準地切割,在采摘面的茶芽識別時采用2次最大類間差分法。首先獲取采摘面的圖像,利用B分量的閾值分割出茶葉區(qū)域;然后選取G和G-B分量的閾值,從茶葉區(qū)域中再分割出嫩茶區(qū)域;最后計算采摘面上嫩茶部分所占面積比例,以70%作為視覺伺服的控制基準。試驗研究表明,提出的基于機器視覺的乘用式采茶機的嫩茶自動識別與采茶機割刀的自動調平調高控制方法能有效解決目前機采茶葉老嫩一刀切下的弊端,為今后全自動化茶葉采摘奠定了基礎。

    Abstract:

    Presently, teaplucking machine has a disadvantage that it cuts indiscriminately without identification of the tender tea. In order to solve this problem, a kind of teaplucking machine was designed based on machine vision. A method was put forward to cut intelligently fused with position servo, visual servo and levelness servo. The cutting line was kept consistently with tea ridge and the header of machine was consistent with horizontal plane by levelness servo. The initial height of the cutter was set by position servo. In order to make the cutting more precise, PID algorithm was used to obtain highly subtle measurements. In terms of visual servo inspection, firstly, tea images of picking surface were taken and the threshold of B component in RGB was used to eliminate background and segment the range of tea. Secondly, the thresholds of G and G-B components were analyzed to distinguish tender leaves from the image by improved OSTU (the algorithm of threshold automatically extracted according to the maximum deviation). Template matched method and threshold of R component were useful to identify cutter line. Finally, the proportion of tender leaves area above cutter line in the image was calculated and its height was adjusted to ensure the ratio above 70%. Experimental result shows that the proposed method solves present disadvantages of teaplucking machine effectively. Also, the efficiency of picking was improved with reduced labor cost.

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湯一平,韓旺明,胡安國,王偉羊.基于機器視覺的乘用式智能采茶機設計與試驗[J].農業(yè)機械學報,2016,47(7):15-20. Tang Yiping, Han Wangming, Hu Anguo, Wang Weiyang. Design and Experiment of Intelligentized Tea-plucking Machine for Human Riding Based on Machine Vision[J]. Transactions of the Chinese Society for Agricultural Machinery,2016,47(7):15-20.

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  • 收稿日期:2016-01-11
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  • 在線發(fā)布日期: 2016-07-10
  • 出版日期: 2016-07-10