Research On Quality Control And Monitoring System Of Automatic Laying Of Composite Materials

Due to its high efficiency,flexibility,quality and low material waste,automated fiber placement(AFP)process has distinct advantages over other kinds of automated manufacturing processed for large and complex composite parts,such as S shaped in-let,fuselage and central wing box.However,the development of AFP in China is still in early stage and most of studies on AFP are concerned about basic areas,including AFP machine configuration and trajectory generation.Research on Quality control and intelligent optimization of process parameters during AFP is not yet in-depth,at the same time,not only effective storage for the AFP of operational information and the abnormal data in the process,but also real-time monitoring of process parameters in the AFP and other related software use are still in a blank state.This paper focuses on the theory of the quality control during AFP and intelligent parameter optimization.It provides a theoretical basis for AFP of quality control,optimization and industrial application.At the same time,developed a set of real-time monitoring system for process parameters to improve the control of AFP on the site.First,the mechanism of prepreg bonding between layers was discussed.The resin flow infiltration model and the self-bonding model are established,and the calculation formulas of the influence of process parameters on the bonding between the prepreg layers are deduced.Through the analysis of the model,The general rule of influence provides a guide for the choice of process parameters.Secondly,through the modeling analysis of the quality control in the process of AFP,several control schemes are put forward.By comparing the advantages and disadvantages and the feasibility,I choose the "process sensitivity control" and "the feedback system parameter control",and think of them as quality control theory,it is used to optimize the current control scheme,which can effectively ensure that the process parameters remain stable during the time-dependent AFP process and plays an important role in the quality stabilization of the structural parts.Thirdly,Based on BP neural network and PSO algorithm(Particle Swarm Optimization),the process parameters were optimized.The three-factor three-level method was used to conduct the multi-factor coupling experiment and the interlaminar shear strength test was carried out.Thus several experimental data were obtained.I use it as neural network training data and confirmatory data.Based on the obtained neural network model,this algorithm is used as fitness function of particle swarm optimization algorithm to optimize the process parameters.The optimal process parameters and the interlaminar shear strength under this parameter are obtained To improve the mechanical properties of the product and reduce the impact of process parameters on the placement quality,for ensuring the performance of structural is of great significance.Then,the process parameter data acquisition system is modeled,and the process parameter acquisition and transmission scheme is designed.By analyzing and solving the key technologies in the system development process,Visual C ++ 6.0 is used as the system development software.The MSComm and TeeChart Pro ActiveX plug-ins are respectively used as serial port communication of the control and dynamic curve drawing control to achieve real-time and efficient collection and dynamic curve monitoring process parameters in AFP.Thus we can able to achieve the abnormal process parameters in the AFP of the alarm to put the process of AFP on the site of the control.Finally,planning the data storage system function module and completing design of the database and table.Database software SQL Server2008 as the background database,Visual C++6.0 as the interface development software for data storage system development.The ADO objects are used for database operation programming to realize the reliable storage of the abnormal operation parameters during the AFP operation information and AFP process and greatly improve the traceability of the AFP process.Make The follow-up evaluation of the quality of the placement be possible.