Author:
Chai Xiaoyu,Xu Lizhang,Li Yang,Qiu Jie,Li Yaoming,Lv Liya,Zhu Yahui
Abstract
One of the most important means of improving the mechanization of rapeseed harvests and increasing farmers’ income is to reduce the cleaning loss of rapeseed. In this study, a fuzzy grey control system was developed using an assembled cleaning loss sensor. Based on experimental data, the relationship between the cleaning loss and the opening of the louver sieve in the cleaning device was obtained. The fuzzy control scheme was established by combining grey prediction and the fuzzy control principle. Secondly, a microcontroller unit (MCU) was used as the controller, and the opening of the louver sieve was automatically regulated by detecting the signal of the cleaning loss. Finally, the performance and robustness of the control system was evaluated in field tests. Different experiments were conducted under different speed conditions to reflect the variable throughput. Results showed that using the grey prediction control system can realize the adjustment of the louver sieve opening in real time. The cleaning loss could be maintained within the ideal setpoint interval, compared with the operation with the control system switched off. These findings indicate that the application of the grey fuzzy control system reduces cleaning loss, and the nonlinear, time-variable and time delay problems in cleaning devices can be solved effectively.
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Reference35 articles.
1. Design of main working parts of 4LYB1-2.0 rape combine harvester;Xu;Trans. CSAM,2008
2. Sensor for monitoring rice grain sieve losses in combine harvesters
3. Dynamic analysis of grain impact on grain loss sensor of combine harvester;Wang;J. Agric. Mech. Res.,1997
4. Design of intelligent grain cleaning losses monitor based on array piezocrystals;Mao;Trans. CSAM,2010
5. Chaos detection of grain impact at combine cleaning loss sensor;Gao;Trans. CSAE,2011
Cited by
12 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献