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秧苗中石子智能化在线监测

Intelligent Online Monitoring for Stone in Rice Seedlings

  • 摘要: 针对分插机构遇到石子、金属块等硬物时,导致分插机构离合器脱开而无法插秧,如不能及时发现导致秧苗漏插等问题,提出了一种通过反射式光电传感器对分插机构转速进行监控从而实现对秧苗中石子进行实时监控的方法,并设计了一种低成本、智能化秧苗石子实时监测系统。为提高监测系统对多尘、泥水环境的适应性,设计了以透明防尘罩和喷头为核心的自清洁除尘装置,以降低尘土、泥水对传感器的干扰。开发了集石子检测、声光报警、除尘控制等为一体的硬件电路和软件算法,实现了对复杂作业环境下石子的实时检测与报警、秧箱剩余秧苗量监测及实际插秧面积的计算。试验结果表明,对秧苗石子等硬物监测准确率为94.4%,剩余秧苗量和实际插秧面积监测的相对误差分别低于7.9%和4.4%,系统对插秧面临的泥水环境具有很强的抗干扰性和可靠性。监测系统可应用于人工驾驶插秧机和无人插秧机,可为无人插秧机作业状态参数监测提供理论基础和实践经验。

     

    Abstract: The clutch of transplanting mechanism was detached and thus the rice transplanting was unable to continue when transplanting mechanism contacted the hard objects such as stone and metal.The miss of seedling transplanting happened if the hard objects in seedlings was not detected in time.In order to break through this technical bottleneck, a low-cost, intelligent and real-time monitoring system for stone in seedlings was developed.To improve the adaptability of monitoring system to dusty and muddy environment, a self-cleaning device based on transparent dust cover and nozzles was designed, which decrease the interference from dust and muddy and increase the sensor accuracy.The hardware and software algorithm were developed for stone detection, sound-light alarm, self-cleaning dust control and so on.The real-time detection for stone and corresponding alarm, monitoring for the remaining seedling amount in seedling box and the calculation of practical transplanting area were meanwhile realized under complicated working environments.Experimental results showed that the monitoring accuracy of the system for rocks and other hard objects in seedlings was 94.4%,the relative error for monitoring the amount of remaining seedlings and the actual area of seedling transplanting were less than 7.9% and 4.48%, respectively.The system has strong anti-interference and reliability to the muddy water environment in practical field conditions. The designed monitoring device can be applied to artificial driving rice tranplanter and unmanned transplanter, which provide theoretical basis and practical experience for detection of working status parameters on unmanned transplanter.

     

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