The Study On Ginning Technology And Digital Monitoring System Of Unginned Cotton

At present,with one belt,one road and the economic type changing,new opportunities and requirements for many traditional industries are also provided.Cotton processing industry is no exception,which brings huge economic demand and huge demand for processing methods.China's cotton processing mode has a lot of manpower from cotton picking to processing,especially the extensive processing mode,which has brought huge economic waste.At the same time,the cotton production efficiency and the quality of finished cotton can not keep up with the demand of the times indirectly.Therefore,how to produce high quality cotton with high efficiency and intelligent mechanization and how to improve the ginning process in production have become the problems faced by cotton processing enterprises.In this paper,through the research on the important ginning process links and digital monitoring system of cotton processing industry in combination with the national key research and development program "key technology and equipment research and development of intelligent control of cotton processing complete equipment"(subject No.:2018YFD0700401),the problems of equipment stability,cotton fiber loss and cleaning efficiency in ginning are found.Using three-dimensional fluid simulation,BP neural network ginning modeling,genetic algorithm to optimize the ginning model,the scheme of air flow type seed cotton cleaning and GA-BP ginning model neural network digital monitoring system is designed to solve the problems of seed cotton cleaning efficiency,cotton fiber loss,stable operation of equipment,and ultimately improve the quality of finished cotton.The main contents of this paper are as follows:(1)This paper studies the ginning process and its mechanism.By analyzing the pre-treatment process before the seed cotton enters the ginning process through the feeding roller,the process of separating the seed cotton fiber from the seed cotton seed by mechanical force in the ginning process,and the impurity cleaning process of the seed cotton fiber,it is found that the main problems of the equipment stable operation,the cotton fiber damage and the impurity cleaning efficiency exist in the process,And the problem finally affects the quality of finished cotton.(2)In order to solve the problems of cleaning efficiency of impurities and loss of cotton fiber in ginning process,the air flow cleaning scheme of seed cotton was put forward.In this paper,the force and movement of the seed cotton fiber and dust impurity in the air flow seed cotton cleaning pretreatment are analyzed firstly,and then the three-dimensional numerical simulation is used to analyze the flow field and the state of the particles in the air flow seed cotton cleaning.The dynamic model is established,and the condition of the impurity and the cotton fiber discharging is found out by CFD method,and the orthogonal experiment is carried out for the influencing parameter,which proves that the numerical simulation is effective to optimize the structure parameters of the equipment,and that the scheme can solve the problems in the process of ginning.(3)A model of digital monitoring system based on BP neural network was established to improve the quality of cotton products.By studying the factors that affect the quality of finished cotton in ginning production,it is found that these factors and the quality of finished cotton have complex non-linear functional relationship.Through the characteristics of BP neural network algorithm,the functional relationship can be effectively learned,and then a digital monitoring model can be established.By using the factory measured data to learn and predict the comparison,it is proved that the scheme is feasible.(4)A scheme of digital monitoring system based on BP ginning model and neural network optimized by genetic algorithm is designed.Because BP network has the characteristics of learning and prediction,there is a big local error in the digital monitoring system.Aiming at this defect,genetic algorithm is used to improve the weight threshold of BP ginning model network and narrow the search field,so as to get a better digital monitoring model,Through simulation analysis,the optimized model has a high degree of fit,which meets the industry requirements.