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| Parameter Identification and Optimization of the MFF Model Based on the Particle Swarm Optimization Algorithm |
| TENG Feng-cheng,HAO Yu,LIN Xiao-le |
| College of Electric Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China |
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Abstract Based on the flux theory and Monte-Carlo method, magnetic fluid transmission characteristics are analyzed and the magnetic fluid film (MFF) models of the transmittance and the sensor are established. Using PSO algorithm, the parameter identification of MFF transmission model is carried out. The influences of number of groups, iterations, inertia weight and acceleration factors on operating results of algorithm are analyzed, and the best combination of parameters is selected. The experiment platform of MFF current sensors is built, the impact of MFF transmission of the MFF thickness and particle concentration is analyzed. The results of experiment and simulation show that the predictive error of the model within 2.3% and the measurement sensitivity of the MFF current sensor reach 12 μW/A.
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Received: 21 December 2015
Published: 28 February 2017
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2017, Vol. 38 
