Study On Sensor Design And Signal Processing Of Magnetically Controlled Shape Memory Alloy

Magnetic controlled shape memory alloy is a kind of new functional materials of reversibility, it exerts higher frequency dynamic force on MSMA material deformation under a bias magnetic field, detection on both ends of the coil output larger induction voltage signal, which can develop MSMA sensor. The design study of sensors based on Magnetic controlled shape memory alloy(MSMA) inverse features is one of the important research content in the field of automatic detection technology and motor control. This paper mainly studies the MSMA sensor model, designs the structure of the MSMA sensor prototype and processes the MSMA sensor signal based on wavelet analysis.Firstly, the MSMA sensors inverse model was established and induced voltage output expression of MSMA sensor was deduced through using MSMA inverse characteristics in this paper. Under the unchanging conditions of the pre-pressure and the bias magnetic field, relationship which was between the frequency of the exciting force and induced voltage was studied.Secondly, the structure of the MSMA sensor was designed on the base of MSMA sensor theory. MSMA sensor size bias magnetic field controllable was analyzed, the core of MSMA sensor optimization structure was determined and MSMA sensor prototype was produced and MSMA sensor experimental system was built by using the simulation results of Mag Net electromagnetic simulation software. MSMA sensor induced voltage of the experimental results and the theoretical results were compared, which verifies the feasibility of the MSMA sensor.Finally, the signal processing and fault detection of the MSMA sensor, which was based on wavelet analysis was developed, MSMA sensor induced voltage existed greater interference, the induction signal must be filtered so as to extract valid data. On the basis of the filter principles of wavelet analysis, the algorithm of daubechies 5(db5) wavelet digital filter is selected in this paper, the induced voltage signals is filtered with soft threshold in different frequency, and the fault detection can be realized by wavelet decomposing induction signal of the MSMA vibration sensor. It can be seen from the result of the wavelet filtering and hardware filtering that the wavelet analysis has an ideal filter effect, and the wavelet analysis can be used for signal process and fault detection of MSMA sensor.