Impedance-frequency Response Application Model Study Of Magnetoelastic Resonance Sensors Based On Impedance Method

Magnetoelastic(ME) sensor is a resonant sensor based on the novel giant ME material. The excitation and transmission of its signals are carried out through magnetic field coupling. With the characteristic of wireless, passive, small volume, high sensitivity, it has a very broad application prospects in non-destructive testing and in vivo biological detection etc. Currently, although the theory research on ME sensor detection is increasing, those researches mainly focus on the vibration characteristics or specific application features, the material factors such as the magnetization and sensor size which greatly influence the sensor impedance response are seldom considered.Therefore, this paper proposed an application model of ME sensor based on impedance method, aimed to direct the design and application of ME sensor by analyzing the influence to sensor response caused by the material factors. First of all, through the analysis of the action of applied magnetic field to the sensor, the strain and the state equation of the sensor was deduced. Then according to the sensor vibration feature, the impedance response of the sensor was deduced. Finally, the characteristic parameters of sensor response were analyzed through the equivalent circuit of impedance response. Thus an impedance-frequency response application model which contains actual control factors such as bias magnetic field and ac excitation magnetic field and intrinsic characteristics such as sensor size was finally preliminarily established.In order to test the correctness of the model, experimental study were conduct from the bias magnetic field, ac excitation magnetic field, sensor size, and mass load. The experimental results were basically consistent with the model. And it was indicated that the response of the sensor, the mass sensitivity and the energy conversion rate can be improved by setting the bias magnetic field in practical application. And ac excitation field can be set to reduce the hysteresis distortion and increase the sensor response. In addition, the sensor response can be also improved by reasonably increasing the length and width of the sensor, and etc. These adequately illustrated the practicability of the model, which means the model can direct the ME sensor design and practical applications, and can preliminarily analyze and solve the problems encountered in application.Finally, the existing ME sensor system software has been optimized according to the model and the experimental results. The functions of automatic determination of the optimum bias magnetic field and sensor response parameter calculation were added to the software. And it simplified ME detection settings procedure, which made the ME detection platform more automated, intelligent, convenient for the experiment and further application study.