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Research On Constant Tension Control Of Diamond Wire Saw Cutting Based On RBF Neural Network

Posted on:2022-08-28Degree:MasterType:Thesis
Country:ChinaCandidate:P Z XuFull Text:PDF
GTID:2491306557976279Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
As a hard and brittle material with good semiconductor properties,monocrystalline silicon is widely used in integrated circuit chips and solar cells.Due to the hard and brittle characteristics of single crystal silicon materials,diamond wire saw cutting technology is widely used in the single crystal silicon slicing process.Slicing is the first process for processing monocrystalline silicon wafers,and the quality of the slicing directly determines the subsequent processing cost and efficiency.Studies have shown that wire tension fluctuations during the diamond wire saw cutting process will affect the processing quality of the workpiece.In order to improve the surface quality of the slices,it is necessary to study the effective control of saw wire tension.In order to further reduce the tension fluctuation of the saw wire and improve the surface quality of the slicing,this thesis conducts research on the constant tension control of the saw wire by designing a tension control device,proposing a control strategy,building a control system and experimenting.The main work content is as follows:First of all,optimize the wire feeding system,preliminarily determine the design plan of the tension control device,optimize the structural plan through Ansys Workbench transient dynamics analysis.Complete the mechanical structure design and equipment selection of the tension control device,build the mechanical part of the constant tension control system.Secondly,through mathematical modeling,analyze the influence of three factors which include the radius jump of the guide wheel and the wire winding wheel,the wire movement of the wire winding wheel and the start and stop commutation of the motor on the tension of the saw wire,provide theoretical basis for the design of control algorithm.Establish a mathematical model of the tension control system,design a control algorithm based on RBF neural network PID self-tuning for the aim of providing control strategy for the construction of constant tension control system.The simulation result shows that the control system using this control algorithm has no obvious tension overshoot,the system stabilization time is 16.5ms,and it also has strong adaptive ability and anti-interference ability in the face of sudden tension changes.Thirdly,select the controller,complete the connection and debugging of the hardware system,complete the programming and data interaction of the software system.According to functional requirements,carry out the development of the host computer control interface.Complete the construction of the constant tension control system.Finally,design the tension control experiment,compare the tension control effect and slice surface quality under pneumatic and constant tension control.The experiment shows that the tension fluctuation of the saw wire under constant tension control is smaller,and the surface quality of the slice is higher.Design single factor experiments of wire speed,workpiece feed speed and target tension value,explore the influence of process parameters under constant tension control on tension control and surface roughness,on this basis,design orthogonal experiments to optimize process parameters.The experiment shows that the surface quality of the slices after the optimization of the process parameters has been further improved.
Keywords/Search Tags:Monocrystalline silicon, Diamond wire saw, Tension control, RBF neural network, PID control, Process parameters
PDF Full Text Request
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