吉林大学学报(信息科学版) ›› 2020, Vol. 38 ›› Issue (5): 555-562.

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基于 Flex 传感器的免耕播种机播深智能调节系统

周淑辉1a, 王增辉2, 黄东岩1b   

  1. 1. 吉林大学 a. 汽车工程学院; b. 生物与农业工程学院, 长春 130022; 2. 东北师范大学人文学院 理工学院, 长春 130117
  • 收稿日期:2020-05-25 出版日期:2020-09-24 发布日期:2020-10-21
  • 通讯作者: 王增辉(1956— ), 男, 吉林磐石人, 东北师范大学人文学院教授, 硕士生导师, 主要从事应用数学研究, (Tel)86-13014307664(E-mail)wzh195693@126.com.
  • 作者简介:周淑辉(1967— ), 女, 黑龙江甘南人, 吉林大学高级工程师, 主要从事电动汽车节能与控制技术及实验教学研究, (Tel)86-13104300638(E-mail)shzhou@jlu.edu.cn
  • 基金资助:
    吉林省科技发展计划基金资助项目(20190802035ZG)

No-Till Planter Sowing Intelligent Depth Regulation System Based on Flex Sensor

ZHOU Shuhui 1a, WANG Zenghui 2, HUANG Dongyan1b   

  1. 1a. College of Automotive Engineering; 1b. College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China;
    2. College of Science and Engineering, College of Humanities & Sciences of Northeast Normal University, Changchun 130117, China
  • Received:2020-05-25 Online:2020-09-24 Published:2020-10-21

摘要: 为了改善免耕播种机的作业性能, 提高播深控制精度, 设计了一套主动作用式智能调节系统。 采用 3 个呈 120°安装在限深轮内壁的 Flex 传感器实现播种单体对地压力的监测。 同时, 采用空气弹簧作为对地压力调节机构, 并以 Mamdani 模糊算法建立了其智能调节模型, 可实现播种单体对地压力的调节, 进而确保播深适宜。 Simulink 仿真结果表明, Mamdani 模糊模型具有良好的播种单体对地压力变化跟随性, 满足播深调控需求。田间试验结果表明, 作业速度为 9 km/ h 时, 系统的播深控制误差较被动调节方式降低了 40% , 实现了播深作业性能的改善。

关键词: Flex 传感器, Mamdani 模糊模型, 播种深度, 智能调节

Abstract: Sowing depth has an important impact on the performance of no-till seeder, it is one of the key factors to ensure the rapid germination. However, the consistency of sowing depth is easily affected by the complex environment of no tillage. The Flex sensor was installed on the inner surface of the gauge wheel at 120° intervals to monitor the pressure exerted by the seeding row unit against ground. The pneumatic spring is used as a down force generator, and its intelligent regulation model is established by Mamdani fuzzy algorithm, which can realize the control of the pressure exerted by the seeding row unit aganst ground and ensure the proper seeding depth.
The working process is simulated based on Simulink, The results show that Mamdani fuzzy model has a good following performace of the pressure change against ground. meet the demand of sowing depth regulation.Experiment results in the field show that, when the working speed is 9 km / h, The control error of the system is 40% lower than that of the passive control, the performance of sowing depth was improved.

Key words: Flex sensor, Mamdani fuzzy model, sowing depth, intelligent adjustment

中图分类号: 

  • TP273