Design Of Yarn Constant Tension Control System Based On STM32

The textile industry has always played an important role in the national economy,especially in the reform and opening up,the textile industry has a rapid development.In the daily life,the consumer's demand for the quality of textile is also getting higher and higher.In the spinning process,the effective control of the yarn tension is a key technology,because the tension will directly affect the quality of the subsequent production of the textile.The control of constant tension of yarn by means of automation has become the current trend of development.The ultimate goal of textile automation is to improve production efficiency and reduce labor consumption.This subject is to control the yarn tension in the winding process as the starting point,in depth analysis and study of tension fluctuation in production process,a solution of yarn tension control system with high performance and expansibility is presented.It is a great significance to the automatic control of yarn tension.Yarn tension control system designed in this paper based on STM32F103ZET6 chip as its control core,including the research background and significance,control algorithm,hardware design,software design,experimental analysis and summary content.The control algorithm introduces the basic principle of PID control and the parameter setting method of adaptive PID based on BP neural network.The hardware design includes the measurement of tension,tension control,chip selection and related circuit design.Software design includes data acquisition,data processing,data display and so on.In the tension control process,the data was collected and filtered,and then according to the yarn tension collected with the preset tension value of error analysis,using the BP neural network adaptive PID technology to control the motor acceleration and deceleration to constant yarn tension.The whole control system contains the speed detection,temperature measurement and other auxiliary functions,which makes the system practicability has been improved.At last,the performance of the system is verified through online experiments and the results are achieved.In addition,the feasibility of the system applied to the industrial field is analyzed,and the problems in the project are summarized.