4.7 Article

Design and implementation of Intelligent transplanting system based on photoelectric sensor and PLC

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.future.2018.05.034

关键词

Intelligent agricultural; Transplanting system; Automatic recognition; PLC control; Logic programming

资金

  1. National Key Research and Development Program of China Sub-project [2016YFD0700103, 2017YFD0700800]
  2. Innovation Scientists and Technicians Troop Construction Projects of Henan Province, China [184200510017]

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Industrial seedling rearing is an important part of seedling transplanting technique. At present, there exists the phenomenon that soil base on the tray may have empty seedling on it, which will lead to a large number of leakage and reduce the yield in the course of automatic transplanting in the field. To solve this problem, automatic seedling identification method is studied to skip picking empty soil bases. An intelligent transplanting system are designed with the use of the picking mechanism five-bar and fixed-axis gear train, the seedling tray conveying mechanism (with transverse and longitudinal seedlings feeding function), the eccentric disk parallel four-bar duck mouthpiece planting mechanism, the electric sensor for seedling detection and identification of the seedling tray, the position sensor, stepper motor and PLC control system. By use of computer logic programming and control, it can be used to identify effectively whether the soil base is empty or not, and to control the automatic transmission of seedling tray. The tray is moved to quickly skip the action path of the manipulator to avoid the picking of empty soil base. The system was tested by using pepper seedlings on indoor condition. The results showed that when the transplanting frequency was 90/min, the rate of success seedling picking was 88.23% and the leakage rate was 16.46%, which could meet the requirement of pepper transplanting. Compared with the transplanting model without seedling identification, the average rate of leakage was reduced about 12%. The research provides a useful reference for the development of intelligent agricultural transplanting technology and equipment. (C) 2018 Elsevier B.V. All rights reserved.

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