张成梁,李蕾,董全成,冯显英,王昊鹏.机采棉加工过程智能控制与试验优化[J].农业机械学报,2017,48(4):73-81.
ZHANG Chengliang,LI Lei,DONG Quancheng,FENG Xianying,WANG Haopeng.Intelligent Control and Optimization Experiment of Machine-harvested Cotton Processing[J].Transactions of the Chinese Society for Agricultural Machinery,2017,48(4):73-81.
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机采棉加工过程智能控制与试验优化   [下载全文]
Intelligent Control and Optimization Experiment of Machine-harvested Cotton Processing   [Download Pdf][in English]
投稿时间:2017-01-09  
DOI:10.6041/j.issn.1000-1298.2017.04.009
中文关键词:  机采棉  加工  智能控制  参数优化  响应面分析法  遗传算法
基金项目:国家自然科学基金项目(51305164、51405194)和山东省重点研发计划项目(2016GNC110025)
作者单位
张成梁 济南大学 
李蕾 齐鲁工业大学 
董全成 济南大学 
冯显英 山东大学 
王昊鹏 山东大学
山东警察学院 
中文摘要:机采棉杂质含量高,多级籽棉清理和皮棉清理会造成纤维损伤,为综合提高皮棉产品的外观形态和纤维内在质量,提出了对机采棉加工工艺进行过程优化控制的研究方法和试验方案。在充分分析典型机采棉加工流程的基础上,根据最新的棉花质量检测标准,确定杂质面积、杂质颗粒数、反射率、黄度、上半部长度、长度整齐度、短纤维指数、马克隆值、断裂比强度9个参数作为优化目标,建立以加工皮棉产品成交价格最大化的总体优化控制目标。选取对棉花清理有显著影响效果的倾斜式籽清机I和II、提净式籽清机、回收式籽清机、轧花机上部、锯齿式皮清机I和II 7个关键设备的转速作为优化控制变量。采用监控层、控制层、设备层的构架模式,完成关键设备自动化升级改造。使用响应面分析法的中心组合设计试验方法建立控制变量与控制目标之间的数据模型。以建立的总体优化控制目标为适应度评价函数,利用遗传算法完成对多变量数据模型的求解,7个设备的转速分别为495、484、727、472、1131、822、763r/min。试验结果表明,加工后的皮棉产品杂质面积变化率降低约7个百分点,上半部长度变化率提高约2个百分点,质量较为稳定。本文方法在降低机采棉含杂率的同时,提高了棉花的综合质量水平。
ZHANG Chengliang  LI Lei  DONG Quancheng  FENG Xianying  WANG Haopeng
University of Ji’nan,Qilu University of Technology,University of Ji’nan,Shandong University and Shandong University;Shandong Police College
Key Words:machine-harvested cotton  processing  intelligent control  parameter optimization  response surface methodology  genetic algorithm
Abstract:The machine-harvested cotton was processed through multistage seed cotton cleaning and lint cleaning, and cotton fiber was damaged inevitably. With the balance of appearance quality and inherent quality, the research method and testing program for process optimization control of machine-harvested cotton processing technology were proposed. According to the latest cotton quality inspection standard, nine parameters optimization targets such as trash area, trash count, reflectance, yellowness, upper half mean length, length uniformity, short fiber index, micronaire and strength were determined, and global optimization goal for the maximum transaction price of lint processing products was established. Seven rotational speed variables of cleaning machines, including inclined seed cotton cleaners I and II, recovery seed cotton cleaner, upper cotton gin, stripper and stick cleaner, saw lint cleaners I and II were selected as optimized control variables, which had significant effect on cotton cleaning. Architecture model based on monitoring layer, control layer and equipment layer was adopted, and upgrading key equipment automation was completed. The data model between control targets and control variables was built by using central composite design of response surface methodology. Taking global optimization control goal as fitness evaluation function, genetic algorithm was proposed to calculate the multivariate data model solution. Seven rotational speeds were 495r/min, 484r/min, 727r/min, 472r/min, 1131r/min, 822r/min, 763r/min, respectively. The test results showed that the change rate of trash area for processed lint products was reduced by 7 percentage points, the change rate of upper half mean length was increased by 2 percentage points, and product quality was more stable. The suggested method guaranteed fiber quality effectively with reduction of impurity content.

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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