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Design And Research On Tension Control System For Stranded Wire Helical Spring NC Machine Tools

Posted on:2018-02-17Degree:MasterType:Thesis
Country:ChinaCandidate:Q ZhangFull Text:PDF
GTID:2321330533961089Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
A stranded wire helical spring(SWHS)is a cylindrical helical spring wound by a cable(twisted in single or multi-layer by several wires).Compared with a conventional single wire helical spring,although the spring has excellent performance in stiffness,fatigue life,vibration reduction,reliability and so on,it is rarely applied in the general products while it is only used in military equipment,which results from tough and complex processes of the design and manufacturing of the spring.In recent years,with the focuses on the product safety,reliability and stability from the ordinary users,the application of stranded wire helical springs in common market gradually causes attention.Therefore,improving the manufacturing efficiency and pass rate,reducing the manufacturing cost are of great significance to promote the application of the springs.However,the main reason for the unqualified products is the inconsistent tension of wires,in the manufacturing process of the springs.Aiming on improving the precision of wire tension control in the manufacturing process of stranded wire helical springs,the researches on tension control system design,system properties analysis,tension control algorithms design and the realization of the tension control system of stranded wire helical spring NC machine tools have been carried out.The following achievements will be introduced in detail:(1)A scheme of tension control system for stranded wire helical spring NC machine tools is proposed by considering the requirements of the tension control in the manufacturing process of the springs.The mechanical structure and electrical control circuit design have been completed based on the scheme of the system.(2)The theoretical model of the wire tension which contains dynamic model of the unwinding reel,tension generation mechanism model and mechanism of interaction between wire tension is proposed based on the wire tension control of the NC machine tool.The simulation model established in Simulink verified the properties: time-varying and interaction between wire tension in the manufacturing process of the spring.And the properties of the tension control system in the prototype NC machine tool are studied by experiments.It is found that the hysteresis effect of the resistance torque on the reel is much large,the detection value consists the gravity component and centrifugal force of detection device,wire tension fluctuation increases with the increment of the process parameters.(3)Considering the properties of the tension control system of the NC machine tools,the PI neural network(PINN)based on slave computer and the fuzzy neural networks based on master computer are proposed with different hardware as computing cores.The experiments with different process parameters and different control methods(incremental PI,PI-PSO,MPIDNN)are conducted to compare with the results of the methods proposed in the thesis.Then the effectiveness of the two methods proposed in the thesis are verified.With the comparing between the two methods,the PINN control scheme based on slave computer has a good economy property while the fuzzy neural networks has a better precision of the wire tension control.(4)The scheme and the corresponding implementation process of the software of tension control system are proposed based on the control structure and requirements of the tension control system in the NC machine tools.The time domain compensation method based on the detection model is designed to reduce the influence of the gravity and centrifugal force of the detection device.And the residual compensation error is mainly due to the phase error and fitting error of the detection model parameters.
Keywords/Search Tags:Stranded wire helical spring, Tension control system, Time-varying and nonlinear system, PINN, Fuzzy neural network
PDF Full Text Request
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