【作者】 王昊鹏；

【导师】 冯显英；

【作者基本信息】 山东大学 ， 机械电子工程， 2014， 博士

【摘要】 棉花从采摘下来的籽棉到加工成皮棉产品大体需要经历3个加工过程,分别是准备、加工和打包。其中,准备过程是指烘干并清理籽棉,也被称为籽棉预处理过程。这一过程主要有两个任务。第一是调整籽棉回潮率,籽棉最适合加工的回潮率是6.5～8.5%,回潮率过低会使棉纤维刚性降低,清理时容易将棉纤维拉断,回潮率过高会增大棉纤维与杂质之间的摩擦力,使得杂质不容易被清理。第二是清除杂质,赴轧籽棉应含有尽可能少的杂质,所以在籽棉预处理过程中应尽量多的清理籽棉中的杂质,但过度的清理也会导致棉纤维损伤,从而降低最终棉花产品的质量。我国棉花种植密度很大,每亩可达到16000～18000株。过密的种植方式给籽棉清理工作带来很多难题。目前棉花采摘大多使用机械采摘方式,由于种植过密,很多棉枝、棉叶、铃壳无法脱落,跟随籽棉一起被采摘。因此棉花加工企业收购的籽棉含杂可高达到20%以上,这就加重了籽棉清理工作的负担。目前我国棉花加工企业的籽棉预处理加工较为落后,主要体现在检测方式落后、加工设备智能化程度低等方面。当前棉花加工企业主要的加工方式是在加工前根据对籽棉的抽检结果调整籽棉预处理设备的关键参数,在加工过程中这些参数不再进行调整。这是一种粗犷的加工方式,设备运行参数无法根据籽棉性状进行实时调整,预处理后的籽棉回潮率一致性差、杂质含量高、棉纤维损伤大,严重影响了最终皮棉产品的质量。尤其是在加工的后期,新疆12月份的气候环境非常恶劣,严重影响了籽棉回潮率等性状,若按前期的加工方案和设备参数加工,则籽棉预处理后的含杂量和回潮率根本达不到轧花加工的要求。针对这些问题,本文对籽棉预处理过程中的籽棉含杂量在线检测、籽棉烘干工艺、籽棉清理工艺等关键问题进行了研究,并设计了籽棉预处理智能控制系统。进行的主要工作如下：(1)根据干燥理论,对籽棉烘干机理进行了研究分析。设计了籽棉热风烘干试验和微波烘干试验,通过试验结果对比分析,提出基于微波-热风联合烘干方式。通过设计的微波-热风联合烘干正交旋转试验建立了籽棉烘干多目标优化控制模型,改进后的烘干工艺有效克服了热风烘干延迟大、能耗大、污染大等缺陷,实现籽棉烘干的多目标优化控制。(2)构建了一种籽棉含杂量在线检测装置,该装置主要由CCD工业相机、镜头、光源和采样机构组成。通过CCD工业相机对籽棉进行图像采样,为保证采样的准确性,该装置的光源必须能提供充足、均匀的光线。采样的图片经过以太网传递给上位机进行图像处理分析。本文在对大量籽棉和杂质采样照片的分析基础上提出了一种基于纹理的籽棉含杂量在线检测算法,该算法不仅可以精确计算出籽棉的含杂总量,还可以识别杂质的种类,以及每种杂质的含量,为实现籽棉清理智能控制奠定了检测基础。(3)对籽棉清理机理及现有清理设备进行了分析,发现不同清理设备主要清理的杂质种类不同,同一清理设备在不同的清理工艺环节中清理效率不同。根据这一特点将所有籽棉清理设备按照工艺环节排序,并将其看成一个整体。分析提取了对棉纤维产生损伤和影响籽棉清理效率的因素,其中最主要的有：一级倾斜式籽棉清理机刺钉滚筒转速、提净式籽棉清理机锯齿滚筒转速、二级倾斜式籽棉清理机刺钉滚筒转速和回收式籽棉清理机刺钉滚筒转速,以这些因素为条件设计了正交旋转试验,通过试验结果建立了籽棉清理多目标优化模型,实现籽棉清理的多目标优化控制。(4)根据本文建立的籽棉烘干和清理多目标优化模型以及籽棉预处理设备的特点设计了籽棉预处理智能控制系统。该系统的硬件结构采用管理层、监控层和现场层3层结构,各层之间采用工业以太网和现场总线相结合的组网技术。该系统软件的控制策略是在建立的籽棉烘干和清理多目标优化模型的基础上提出的籽棉预处理智能控制策略,该智能控制策略以混沌粒子群优化算法为基础,结合籽棉预处理过程的特点,将粒子群进行分组初始化,并对启动混沌机制的判断进行了改进,经过实际生产检验,该智能控制策略能对籽棉预处理过程进行有效控制,优化了预处理过程中各设备运行参数,使籽棉的回潮率一致性更好、含杂量更低、棉纤维损伤更小。本文的研究为籽棉预处理加工提供了重要的理论和技术支持,为实现棉花精细化加工提供了解决方案,对提高我国棉花加工业自动化和智能化水平有较大的理论意义和实际应用价值。更多还原

【Abstract】 From being picked to be processed into finished products, cotton generally experienced3processes. They are preparing, processing and packaging. Among them, the preparation process included seed cotton drying and cleaning, also known as the seed cotton pretreatment process. Seed cotton pretreatment process had two main tasks. The first was to adjust the seed cotton moisture regain. Seed cotton moisture regain most suitable for processing was6.5-8.5%. Low moisture regains made cotton fiber stiffness reduction. When being cleaned, the cotton fiber was easy to be broken. Excessive moisture regain would increase the friction between cotton fiber and impurities. So the impurities were not easy to be cleaned. The second was to clean impurities. Seed cotton should contain impurities as little as possible before being ginned. So the cotton processing enterprise should clean the impurities as much as possible in the seed cotton pretreatment process. But excessive cleaning would cause damage to cotton fibers. This could reduce the final quality of the cotton productsChina’s cotton planting density was large, which could reach16000～8000strain per mu. Many difficulties had product during the seed cleaning process because of the high planting density. At present most cotton was picked by harvester. Because of the high planting density, a lot of cotton plant, cotton leaf and boll shell could not take off. They were picked with seed cotton together. Therefore, the cotton processing enterprise purchased the cotton which had high impurities content. The maximum impurities content could reach more than20%. This problem aggravated the burden of seed cotton cleaning work.Now, the seed cotton pretreatment process which was applied in cotton processing enterprises was relatively backward in our country. The problems mainly reflected in the detection way backward and low level of automation processing equipment. At present cotton processing enterprises mainly process was that adjust the key parameters of cotton seed processing equipment according to the sampling results before processing. These parameters were not adjusted in the process. This was a rough processing way. The key parameters of cotton seed processing equipment could not be real-time adjusted according to the seed cotton properties. Seed cotton which was pretreatment had a lot of problems. These problems included cotton moisture regain consistency, high impurity content and cotton fibers damage. All of these problems seriously affected the quality of the final cotton product. Especially in the late processing, the climatic environmental of Xinjiang is very poor in December. This serious influenced the properties of seed cotton. According to the early processing scheme and equipment parameters, the impurities content and moisture regain of seed cotton which were processed were not up to the requirements of ginning processing.Aiming at these problems, this dissertation carried out research into on-line detection of seed cotton impurities content, seed cotton drying process, seed cotton cleaning process and designed the intelligent control system of seed cotton pretreatment. The main research contents of the dissertation area as follows:(1)According to the drying theory, the seed cotton drying mechanism was analyzed. The seed cotton hot-air drying experiment and microwave drying experiment were designed. The main factors affecting the efficiency of drying included temperature of hot air and microwave power density. The control objectives included the drying efficiency, the damage of fiber specific breaking strength, the damage of Rd and the increment of +b. By analyzing the results of experiment, a new way based on microwave-hot air drying was proposed. The improved drying process effectively overcame the defects of hot-air drying, such as high energy consumption, big delay and pollution etc. By the orthogonal rotation experiment, multi-objective optimization control model of seed cotton drying was established. The seed cotton drying multi-objective optimal control was realized.(2)A seed cotton impurities content on-line detection device was constructed. The device mainly consisted of CCD industrial camera, lens, the light source and the sampling mechanism. This device used the Pilot series area of black and white CCD industrial camera manufactured by Basler, type PiA2400-17gm, the CCTV series lenses manufactured by Myutron, type HF0528J. The focal length of lens was5mm, could be tuned to5.5mm. The light source used LED light, which color was white. The device sampled through the CCD industrial camera. In order to ensure the accuracy of the sampling, the device must be able to provide adequate and uniform light. Sampling images were transmitted to the host computer through Ethernet. Then the host computer analyzed these sampling images. By the analysis of seed cotton and impurities sampling images, the dissertation presented a cotton impurity content online detection algorithm based on texture. This algorithm not only could accurately calculate the impurity content of seed cotton, but also could identify the types of impurities. The algorithm laid a foundation for the realization of seed cotton cleaning detection of intelligent control.(3)The seed cotton cleaning mechanism and the existing cleaning equipments were analyzed. The dissertation found that different types of equipments mainly cleaned different types of impurities. The cleaning efficiency of same type equipment was different in different cleaning process. According to this characteristic, this dissertation would all seed cotton cleaning equipment as a whole, and in accordance with the process of sorting. The factors which could affect the cleaning efficiency of seed cotton were analyzed. These factors mainly included the barbed nail roller speed of the two inclined seed cotton cleaners, the sawtooth roller speed of stripper and stick cleaner, the barbed nail roller speed of inclined and recovery seed cotton cleaner. This dissertation designed an orthogonal rotation experiment based on these factors. The control objectives included the reduction of fiber length, the increment of short fiber, the reduction of ginning outturn and the cleaning efficiency of different types impurities. By the results of this experiment, multi-objective optimization control model of seed cotton cleaning was established. The seed cotton cleaning multi-objective optimal control was realized.(4)According to the seed cotton drying multi-objective optimal control model and the seed cotton cleaning multi-objective optimal control model, this dissertation designed a seed cotton pretreatment intelligent control system. The hardware structure of this system adopted3layers structure, including the management layer, control layer and field. Networking between each layer used the industrial Ethernet and field bus combination. The control strategy of this system was an intelligent control strategy. This intelligent control strategy based on the seed cotton drying multi-objective optimal control model and the seed cotton cleaning multi-objective optimal control model. The core algorithm of this intelligent control strategy based on chaotic particle swarm optimization algorithm. The algorithm grouped and initialized particle swarm, and improved the starting mechanism of chaos judgment. According to the actual production test, the intelligent control strategy could effectively control the seed pretreatment process. The parameters of seed cotton pretreatment equipment were optimized. Seed cotton moisture regain was more consistent. Seed cotton impurities content and the damage of cotton fibers were reduced.The dissertation provided the theoretical and technical supports for seed cotton pretreatment process. The method provided a solution strategy to fine processing and helped to realize adjusting according to cotton properties. The study showed theoretical and practical significance to improve t cotton industry automation and intelligent level in China.更多还原