| 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. |
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