Abstract
Magnetically controlled shape memory alloy (MSMA) has a mechanical–electromagnetic inverse characteristic. Based on MSMA inverse characteristics, an identification algorithm on MSMA sensor model parameter is proposed in this paper. When removing the pre-pressure system, the improved sensor structure is proved to be more effectiveness through theoretical and experimental research. In the absence of pre-pressure, chaotic particle swarm optimization algorithm is used to identification each parameter of MSMA sensor model, the model parameter of the sensor is obtained under different experimental conditions. Comparison the experimental and calculated values of the induced voltage, the correctness of model parameter algorithm is verified by this method. The research work lays a foundation for theoretical research of MSMA sensor.
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