棉花播种质量实时监测系统设计与试验

    Design and experiment of real-time monitoring system for cotton sowing quality

    • 摘要:
      目的  针对新疆地区使用的棉花穴播机作业过程中,驾驶员无法及时发现穴播器漏播、重播的问题,设计了一套棉花播种质量实时监测系统。
      方法  该监测系统以STM32F103C8T6微控制器硬件系统为下位机,通过安装在穴播器存种圈上的对射式光电传感器和光电编码器分别获取棉花种子漏播、重播信息,判断棉花播种状况,并通过nRF24L01模块将播种信息传输至DWIN触摸屏上位机人机交互界面实时显示。搭建棉花播种质量监测系统试验台,通过田间试验验证监测系统的准确性。
      结果  台架试验结果表明:当穴播器转速为30 r/min时,系统的合格播种、漏播和重播监测精度最高,分别为96.65%、94.59%和92.00%。当穴播器转速高于30 r/min时,监测精度明显下降。田间试验验证结果表明:系统对合格播种、漏播和重播平均监测精度分别为94.51%、92.38%和86.55%。利用SPSS软件对田间试验数据进行分析,结果显示试验数据具有统计意义,采用监测系统获得的棉花播种质量数据与人工实测数据具有较高的相关性,实际值可以由系统监测值反映出来。
      结论  该系统满足田间作业对棉花播种质量监测的需求,对实现棉花种植提质增效具有重要意义。

       

      Abstract:
      Objective  There are problems of missed seeding and reseeding during the operation of cotton hole sowing machine used in Xinjiang region, which the driver could not find in time. A real-time monitoring system for cotton sowing quality was designed to solve these problems.
      Method  The monitoring system uses the STM32F103C8T6 microcontroller hardware system as the lower computer, obtains the information of missed seeding and reseeding of cotton seeds through the counter-light photoelectric sensor and photoelectric encoder installed on the seed storage ring of the hole sower, and determines the quality of cotton sowing. The cotton sowing information is transmitted to the human-machine interface of the DWIN touch screen through the nRF24L01 module for real-time display. A test bed of cotton sowing quality monitoring system was built to verify the accuracy of the monitoring system through field tests.
      Result  The results of the bench test showed that the system had the highest monitoring accuracies of 96.65%, 94.59% and 92.00% respectively for qualified seeding, missed seeding and reseeding when the speed of the hole sower was 30 r/min. When the speed of the hole sower was higher than 30 r/min, the monitoring accuracy decreased obviously. The results of field trial validation showed that the average monitoring accuracies of the system were 94.51%, 92.38% and 86.55% respectively for qualified seeding, missed seeding and reseeding. The analysis of the field trial data using SPSS software concluded that the trial data were statistically significant, and the cotton sowing quality data obtained by the monitoring system had a high correlation with the manually measured data, and the actual values could be reflected by the system monitoring values.
      Conclusion  The system meets the demand for monitoring the quality of cotton sowing in field operation, and is of great significance for realizing the improvement of quality and efficiency of cotton planting.

       

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