汪凤珠,张俊宁,李瑞川,伟利国,韩湘,刘阳春.花生联合收获机作业在线监测与故障预警系统研究[J].农业机械学报,2015,46(S1):69-73.
Wang Fengzhu,Zhang Junning,Li Ruichuan,Wei Liguo,Han Xiang,Liu Yangchun.Design of On-line Monitoring and Fault Early Warning System for Peanut Combined Harvester[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(S1):69-73.
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花生联合收获机作业在线监测与故障预警系统研究   [下载全文]
Design of On-line Monitoring and Fault Early Warning System for Peanut Combined Harvester   [Download Pdf][in English]
投稿时间:2015-10-28  
DOI:10.6041/j.issn.1000-1298.2015.S0.012
中文关键词:  花生  联合收获机  工况监测  故障诊断  预警
基金项目:山东省自主创新专项资助项目(2013CXC90205)和北京市科技新星计划资助项目(2015A084)
作者单位
汪凤珠 中国农业机械化科学研究院 
张俊宁 中国农业机械化科学研究院 
李瑞川 山东五征集团有限公司 
伟利国 中国农业机械化科学研究院 
韩湘 北京市科学技术委员会农村发展中心 
刘阳春 中国农业机械化科学研究院 
中文摘要:基于4HBLZ-2型单垄小型自走式花生联合收获机,设计摘果辊、清选筛、夹持轴、夹持链以及各转动部件工况的在线检测方法。利用LabView开发了基于CAN1939总线通信网络的花生收获机械作业在线监测系统,实现了整机控制状态、收获模式、发动机参数、行走轨迹、核心工作部件工况等的实时监测;采用多传感器信息融合算法,建立了作业状态的自诊断与故障预警模型,能够在拨果辊堵塞、跑粮及链条断裂等异常作业工况下为驾驶员提供田间实时报警信息。试验表明,本系统达到了花生收获机田间作业工况实时监测的功能和精度需求,且故障预警的自动诊断时间低于2 min,故障检测准确率大于90%。
Wang Fengzhu  Zhang Junning  Li Ruichuan  Wei Liguo  Han Xiang  Liu Yangchun
Chinese Academy of Agricultural Mechanization Sciences,Chinese Academy of Agricultural Mechanization Sciences,Shandong Wuzheng Group Co,Chinese Academy of Agricultural Mechanization Sciences,Rural Development Center of Beijing Municipal Commission of Science and Technology and Chinese Academy of Agricultural Mechanization Sciences
Key Words:Peanut  Combined harvester  Operation monitoring  Fault diagnosis  Early warning
Abstract:In order to improve the automatic operation degree in traditional peanut combined harvester, the online conditions measurement method for key working parts, such as picking roller, sorting screen, clamping shaft, clamping shaft and rotating components, was designed on the basis of 4HBLZ-2 one-row small self-propelled peanut combined harvester. Using LabView, an on-line operation monitoring system of peanut combined harvester was developed, with which the machine control state, harvesting operation mode, engine parameter, harvesting trajectory and working conditions of main parts could be real-timely monitored. The self-diagnosis and fault early warning model was established with the application of multi-sensor information fusion algorithm, which could offer alarm message for drivers under abnormal conditions, such as blocking of picking roller and chain break. Tests result showed that the time of automatic fault diagnosis was less than 2 min and the accuracy of fault detection was up to 90%. The designed system had met the functional requirements and precision needs of peanut combined harvester real-time monitoring in field operation.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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