Research On Ring Spinning Cyber Physical Production System And Its Key Technologies

Ring spinning is the most important yarn production method,which produces yarn with good strength,high evenness and wide range of suitable spinning products.At present,the number of spindles for ring spinning in China has exceeded 137 million,accounting for about 2/3 of the total number of spindles for ring spinning in the world.It is an industry with international competitive advantage.In recent years,it is difficult to recruit workers for ring spinning production,and there is an urgent need for less humanized/unmanned production mode.The competition in the spinning market is fierce,and improving the production capacity of high quality and high reliability yarn is the focus of competition.Due to the variety of production equipment,complex communication interface,and the difficulties of interconnection oriented towards less humanized/unmanned,it is difficult to achieve continuous production in the whole process of ring spinning.In high speed and continuous ring spinning production,it is necessary to deal with various tasks in time to reduce the rate of defective products and waste,and to meet the high real-time requirement of task processing.Due to the long process flow of ring spinning,the yarn quality is affected by many factors such as environment,process and raw materials,and it is difficult to control the quality consistency.Cyber Physical System(CPS)is the core of intelligent manufacturing.However,there is no research on relevant theories,technologies and application methods for ring spinning production characterized by dynamic,high-speed,continuous and batch manufacturing.In this paper,a CPS-based ring spinning system is first proposed.From the system framework to core elements of ring spinning CPPS,the transmission of key process parameters and control instructions,the computation and processing of real-time tasks,yarn quality control and other techniques are studied and applied in practice.The main research content and innovation of the thesis are embodied in the following four aspects:(1)In light of the problems such as long process flow of ring spinning,large changes in fiber morphology,mixing of production continuity and discreteness,and the diverse and complex relationships between data flow and control flow in the production process,the ring spinning CPPS system architecture is systematically studied,the ring spinning CPPS model based on the fusion of "fiber flow-data flow-control flow" is proposed,and its formal definition description is given.Based on MBSE method,the modeling of CPPS for ring spinning is studied.Sys ML is used to establish the demand diagram,use case diagram,sequence diagram for fiber flow,state machine diagram for data flow and time sequence activity diagram for control flow of ring spinning physical production system.(2)In view of the problems such as factory management and control of less humanized/unmanned ring spinning production and the trusted transmission of key process parameters and control instructions,this paper takes the lead in putting forward the trusted transmission method of key process parameters and control instruction of ring spinning based on blockchains.The interconnection system of ring spinning CPPS is studied,a spinning equipment information model based on OPC UA is proposed,and a cloud-side transmission model of key process parameters and control instructions is established.The transmission models of key process parameters and control instructions within and between edge nodes are designed,the blockchain construction method of process parameters and control instructions is studied,and a consensus mechanism of delegated proof of stake based on time-sensitive rewards is proposed,which increased the successful voting rate.(3)Aiming at the problems of real-time processing in high-speed production of ring spinning,this paper proposes a processing method of real-time tasks based on edge computing.Based on the characteristics of ring spinning production,an edge computing node deployment model mixed with n-1 and 1-1 is established,and the collaborative mechanism between edge computing nodes is studied.The real-time task processing models of single edge computing node and all edge computing nodes are studied respectively,and the real-time task processing algorithms are designed,effectively reducing the delay rate of task processing.(4)In view of the many factors influencing yarn quality in ring spinning,the complex coupling relationship,and the randomness of yarn quality fluctuations,a yarn quality control method based on actor-critic deep reinforcement learning is proposed.According to the current situation of ring spinning quality control,from three control strategies of single process,pre-constrained adjacent processes,and global processes,the actor-critic deep reinforcement learning model of yarn quality control based on quality loss function is established,including single process independent control model,nested control model with pre-process constraints,and shared control model of global process,which effectively improves the consistency of yarn quality.Finally,a comprehensive test research of ring spinning production is carried out in this paper.A production test verification scheme is designed to verify and analyze the trusted transmission method of key process parameters and control instructions,the realtime tasks processing method and yarn quality control strategy respectively.The results show that the method proposed in the thesis has a good effect on solving specific problems in ring spinning production.