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清潔車(chē)智能監測與控制系統研究
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西北工業(yè)大學(xué) 自動(dòng)化學(xué)院

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TP3

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Research on intelligent monitoring and control system of cleaning vehicle
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    摘要:

    針對目前市面上的清潔車(chē)容易因為駕駛員的疏忽造成清掃盤(pán)與路沿的碰撞,加速清掃盤(pán)的損壞,灑水作業(yè)容易波及路人,貼地工作的吸盤(pán)容易與減速帶碰撞造成損失,不能自動(dòng)根據垃圾量調節清掃功率等問(wèn)題,提出了一種清潔車(chē)智能監測和控制系統。該系統采用超聲測距模塊避免碰撞,運用YOLOv4算法檢測行人和減速帶,使用VGG16網(wǎng)絡(luò )進(jìn)行垃圾量化進(jìn)而調節清掃功率,通過(guò)CAN通信模塊實(shí)現對清潔車(chē)設備的實(shí)時(shí)控制。該系統采用多線(xiàn)程實(shí)現多任務(wù)算法之間的協(xié)調與通信。行車(chē)實(shí)驗表明,該系統的整體運行速度為每秒6-7幀,滿(mǎn)足實(shí)時(shí)性。路沿距離檢測及避障算法準確率為96%,垃圾量化算法準確率為90%,行人和減速帶算法準確率為96.25%,準確率較高,能夠有效提高清掃效率,降低設備損耗,提高行車(chē)安全。

    Abstract:

    Aiming at the problems that the cleaning vehicle on the market is easy to collide with the roadside due to the negligence of the driver, accelerate the damage of the cleaning plate, the watering operation is easy to affect passers-by, the suction cup working close to the ground is easy to collide with the deceleration belt, resulting in losses, and the cleaning power can not be automatically adjusted according to the amount of garbage, an intelligent monitoring and control system for the cleaning vehicle is proposed. The system uses ultrasonic ranging module to avoid collision, uses YOLOv4 algorithm to detect pedestrians and speed bumps, uses VGG16 network to quantify garbage and adjust cleaning power, and realizes real-time control of cleaning vehicle equipment through Controller Area Network (CAN) communication module. The driving experiment shows that the overall running speed of the system is 6-7 frames per second, which meets the real-time performance. The accuracy of roadside distance detection and obstacle avoidance algorithm is 96%, the accuracy of garbage quantification algorithm is 90%, and the accuracy of pedestrian and deceleration belt algorithm is 96.25%. The accuracy is high, which can effectively improve the cleaning efficiency, reduce equipment loss and improve driving safety.

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熊文軍,趙山虎,李世博,楊建華,范孝波,孫洪良,陳軍.清潔車(chē)智能監測與控制系統研究計算機測量與控制[J].,2022,30(5):109-114.

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歷史
  • 收稿日期:2021-11-09
  • 最后修改日期:2021-12-07
  • 錄用日期:2021-12-08
  • 在線(xiàn)發(fā)布日期: 2022-05-25
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