Research On Micro-displacement Sensor Based On Inverse Characteristic Of Magnetically Controlled Shape Memory Alloy

The application technology based on intelligent materials has become a hot research topic in recent years,many countries have been listed as a priority breakthrough technology.Magnetic shape memory alloy(Magnetic Shape Memory Alloy,MSMA)is a new type of smart materials in recent years was found,the material has high response speed,good repeatability,magnetic field induced strain and stress the advantages of a larger output under the action of the magnetic field is used as the sensing element has great prospects for development.At present,the application of MSMA materials at home and abroad is mainly focused on the field of drives,and there are few researches in the field of sensors.MSMA-based sensing technology and devices need to be further studied.For this reason,this paper explores a new type of intelligent micro-displacement sensor with MSMA as the research object.The main research contents are as follows:(1)The microstructure and deformation mechanism of MSMA materials are analyzed and studied.On this basis,the microscopic mechanism of MSMA micro-displacement sensor is established;in order to solve the problem of MSMA micro displacement sensor signal is difficult to be separated and extracted based on the sensing signal exists----multi-field coupling,the micro displacement measurement method based on frequency in LC,the oscillation circuit frequency model based on the development of external LC oscillation frequency detection of MSMA element deformation micro displacement sensor based on prototype.The simulation and experimental results show that the MSMA micro-displacement sensor has the characteristics of simple system structure and little interference signal.(2)According to the characteristics of MSMA micro displacement sensor output with hysteresis,based on experimental data samples,using hysteresis function link artificial neural network(HFLANN)to establish the dynamic model of the sensor,and using an improved particle swarm optimization algorithm to optimize system identification,reduce system error.The results show that the sensor has the characteristics of simple structure,small error and high sensitivity,and it also provides a new method and idea for the application of MSMA in the field of new type intelligent sensors.