| The machining accuracy of the resistance adjusting machine directly affects the resistance value accuracy of the resistance strain gauge.Therefore,in the production of the strain gauge,the mechanical structure accuracy of the resistance adjusting machine and the performance of the control system are increasingly required.Aiming at the above problems,a high-precision automatic strain gauge resistance regulator is designed.Firstly,the automatic function and high precision machining method are designed,then the mechanical structure and control system are designed,and an improved particle swarm control algorithm is put forward.Finally,simulation verification is carried out in the simulink,and the resistance adjustment experiment is carried out.This thesis mainly from the following aspects:(1)The design method of automatic and high-precision resistance adjusting of the resistance regulator is studied: by measuring the resistance value before the resistance regulator of the strain gauge,feeding it back to the development board,setting the expected resistance value,let the resistance regulator decide the resistance condition according to the expected value,and realize the automatic resistance regulation function of the resistance regulator;research on the design verification of the thermal deformation of the resistance regulator,the guide rail,and the control principle of the creeping and stepping motors,so as to realize the high precision resistance regulation of the resistance regulator.(2)Simulation verification of control system performance.This thesis studies the mathematical model of stepping motor and designs its Simulink control model,which mainly includes the Simulink model of stepping motor,subdivision drive module and incremental PID controller module.After these modules are connected,the control model of stepping motor is obtained,the running parameters are set,and the simulation results are obtained.Through the analysis of the results,it is found that the convergence speed of the system is slow and super fast So it is necessary to optimize the control system.(3)Control system optimization.Firstly,the particle swarm optimization algorithm is optimized,and the hybrid mechanism of genetic algorithm is used for reference to improve the optimization ability of particles;the nonlinear decreasing strategy of inertia factor is used to improve the efficiency of the algorithm;at the same time,in order to avoid the particles crossing the solution space in the process of optimization,the boundary stitching mechanism is introduced,that is,when the particles exceed the boundary,the particles are stitched to get a Four improved particle swarm optimization(BSPSO)algorithms are applied to the designed stepping motor Simulink control model.The simulation results of the two systems are obtained by comparing the simulation results of the unimproved system,which verify that BSPSO algorithm optimizes the control system.(4)Experimental verification of resistance regulator.Debug and verify the completed system,system debugging mainly includes hardware control system debugging,software debugging and joint debugging.Experimental verification is carried out on the resistance regulator,and the experimental data are analyzed by comparing the resistance regulator with or without BSPSO algorithm.The results show that the designed resistance regulator achieves the design precision and the improved BSPSO algorithm increases the resistance regulator precision. |
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