Development Of Two-dimensional Wireless And Passive Force Sensor Based On Magnetostrictive Effect

With the development of sensor technology,the application of multidimensional force sensor is becoming more and more extensive,whether in the field of industrial defense,biological engineering,health care,structural monitoring and other fields,can not do without the application of multi-dimensional force sensor.In order to realize data transmission,the existing multi-dimensional sensors need to be connected with the elastomer structure of the sensor directly.This paper designs and develops a two-dimensional wireless passive force sensor with magnetostrictive material as strain sensitive element combined with wireless passive detection technology,and aims at the wireless passive detection method in the process of sensor measurement.Sensor calibration and static decoupling methods are studied.Firstly,the elastomer structure of two-dimensional force sensor based on magnetostrictive effect is designed.Fe₄₀Ni₃₈Mo₄B₁₈?2826MB?is used as strain sensitive element to realize wireless passive detection of two-dimensional force information of tension and torque.The elastomer structure based on stiffness distribution mainly includes bearing end,torsional strain surface,tensile strain beam,buffer ring structure and fixed end.In the ANSYS finite element static analysis,the strain sensitive region of the sensor subjected to tension and torque is in different positions,which meets the expectation that the sensor itself has certain decoupling ability.The elastomers were fabricated by 3D printing technology and the sensor samples were fabricated.In order to ensure that the sensor detects the tension and torsion two-dimensional force information successfully,a signal detection system is designed for the wireless passive sensor,and the sensor is loading tested.The test results show that the sensor can realize the wireless detection and transmission of two-dimensional tension and torsion forces.Secondly,because the coupling phenomenon between two-dimensional force sensor and even multi-dimensional force sensor is inevitable,it is necessary to reduce the coupling error rate of the sensor.Taking the two-dimensional wireless passive force sensor developed in this paper as the research object,the coupling phenomenon and the necessity of decoupling between the output channels of the two-dimensional sensor are analyzed.On the basis of this,the static decoupling method of the two-dimensional sensor is studied.According to the principle of linear static decoupling method of sensor,the decoupling calculation method based on least square method is deduced.Considering that the sensor is a nonlinear input-output system and the decoupling effect of linear static decoupling method is not complete,the nonlinear static decoupling method based on BP neural network is used to decoupling the sensor.According to the sensor test data,the least square method and the static decoupling method of BP neural network method are used to verify the decoupling of the sensor.The decoupling effect shows that the nonlinear decoupling method based on BP neural network has higher precision.Finally,in order to verify the rationality of the elastomer structure design and the static characteristics of the two-dimensional wireless passive force sensor,the output performance of the sensor is studied experimentally in this paper.According to the calibration experiment of the sensor and the two-dimensional composite force loading experiment,the two-dimensional wireless passive force sensor developed in this paper can detect the two-dimensional force information successfully and effectively.The output curve of the sensor shows that the coupling error between the output channels of the sensor is small,which proves that the elastomer structure design of the sensor is reasonable and can meet the expected design requirements.The hysteresis experiment shows that the input and output of the tension and torque of the sensor have lower backhaul error and the static characteristics of the sensor are good.