| 玉米联合收获机清选损失监测装置设计与试验 |
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| 引用本文： | 王卓,车东,白晓平,胡河春.玉米联合收获机清选损失监测装置设计与试验[J].农业机械学报,2018,49(12):100-108. |
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| 作者姓名： | 王卓 车东 白晓平 胡河春 |
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| 作者单位： | 中国科学院沈阳自动化研究所,中国科学院沈阳自动化研究所;东北大学,中国科学院沈阳自动化研究所,中国科学院沈阳自动化研究所 |
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| 基金项目： | 国家重点研发计划项目（2016YFD0700105-03） |
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| 摘 要： | 针对玉米籽粒收获时，损失率检测不准的问题，以压电薄膜作为敏感材料，设计了一种由冲击传感器、信号处理电路和安装装置等组成的玉米收获机籽粒清选损失监测装置，并采用支持向量机多分类算法提取玉米籽粒冲击信号，实现了玉米籽粒损失的实时监测。首先，在不同冲击角度和高度的试验条件下，对不同大小的玉米籽粒和杂余进行冲击信号的采集试验，提取冲击信号的主要特征。采用支持向量机多分类算法对模型进行训练，并在监测装置上实现实时分类。使用不同品种和含水率玉米对分类模型进行验证。然后，在不同风机转速和清选筛开度条件下，得到测试时间内传感器检测的籽粒数与总损失量之间的关系，并根据谷物流量值，计算得到实时的清选损失率。最后，将该监测装置安装在4YL-8型玉米联合收获机上进行田间试验。结果表明，该监测装置与人工检测相比，平均相对误差为12.98%，可以为收获机的控制提供反馈信息。
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| 关 键 词： | 玉米联合收获机 清选损失 监测装置 支持向量机 压电薄膜 |
| 收稿时间： | 2018/7/10 0:00:00 |
Improvement and Experiment of Cleaning Loss Rate Monitoring Device for Corn Combine Harvester |
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| WANG Zhuo,CHE Dong,BAI Xiaoping and HU Hechun.Improvement and Experiment of Cleaning Loss Rate Monitoring Device for Corn Combine Harvester[J].Transactions of the Chinese Society of Agricultural Machinery,2018,49(12):100-108. |
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| Authors: | WANG Zhuo CHE Dong BAI Xiaoping and HU Hechun |
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| Institution: | Shenyang Institute of Automation, Chinese Academy of Sciences,Shenyang Institute of Automation, Chinese Academy of Sciences;Northeastern University,Shenyang Institute of Automation, Chinese Academy of Sciences and Shenyang Institute of Automation, Chinese Academy of Sciences |
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| Abstract: | Piezoelectric films were used as sensor sensitive materials. A grain cleaning loss rate monitoring device suitable for corn harvesting was designed. The impact sensor, signal processing circuit and mounting device were designed, and the corresponding processing algorithm was used to collect the impact signal. Firstly, under different experimental conditions of impact angle and height, the impact signal acquisition experiments of different sizes of corn kernels and impurities were carried out. The main characteristics of impact signal were also extracted. Secondly, the support vector machine was used for multi-classification. The model was trained by the support vector machine multi-classification algorithm and real-time classification was implemented on the monitoring device. And the classification model was validated by using different corn varieties and moisture content. Then, under the conditions of different fan speeds and cleaning screen opening degrees, the relationship between the number of grains detected by the sensor and the total loss during the test time was obtained. And the real-time cleaning loss rate was calculated according to the grain flow value. Finally, the monitoring device was mounted on a 4YL-8 combine harvester and field trials were conducted. The results showed that the average relative error of the monitoring device compared with manual detection was 12.98%, which can provide feedback for the control of the harvester. |
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| Keywords: | corn combine harvester cleaning loss monitoring device support vector machine piezoelectric films |
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