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Design And 3D Force Prediction Of Piezoelectric Tactile Sensor Based On PVDF

Posted on:2022-04-04Degree:MasterType:Thesis
Country:ChinaCandidate:Y F ChenFull Text:PDF
GTID:2518306494488754Subject:Engineering
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With the development of robot technology,intelligent robots have higher and higher requirements for tactile sensors,which makes tactile sensors develop rapidly.Domestic and foreign researchers have successfully developed many excellent tactile sensors,but there are still many problems to be solved.Aiming at the problems of traditional tactile sensors such as low sensitivity and difficulty in effectively identifying three-dimensional forces,this paper combines the piezoelectric material PVDF with the flexible material PDMS.Starting from the sensor structure design and material selection,a piezoelectric tactile sensor similar to a "sandwich" structure is designed.The main research contents of this paper include the following four aspects.(1)In this paper,the working principle of piezoelectric sensor is studied,and the piezoelectric effect and piezoelectric equation are analyzed in detail.Starting from the structural design of the tactile sensor,polyvinylidene fluoride(PVDF)was selected as the piezoelectric material to design the piezoelectric tactile sensor,and polydimethylsiloxane(PDMS)was selected as the protective layer of the piezoelectric tactile sensor.A new type of "sandwich" piezoelectric tactile sensor was designed.(2)Combined with the finite element analysis technology,the multi-physical field simulation of the piezoelectric tactile sensors with different structures is carried out,and the simulation results of the detected sensitive units are analyzed and discussed.In this paper,the stress of different piezoelectric tactile sensor structures(cylinder type,circular type sensor)under the action of tangential force and normal force is studied.Different forces are applied on the surface of the piezoelectric tactile sensor,and the stress,voltage and sensitivity of the sensor are compared and analyzed.The experimental results show that under the same size of tangential force and normal force,the sensitivity of the circular type sensitive element is obviously higher than that of the cylindrical type sensitive element,and the experimental effect is better.(3)A piezoelectric tactile sensor array is designed based on the circular sensor unit.The performance of piezoelectric tactile sensor array is analyzed from different angles by using finite element analysis technology.The voltage variation of the sensor unit under different tangential force and normal force is studied.The effects of the height of the sensing element,the ratio of the radius of the bottom surface to the radius of the top surface and the electrode material on the sensitivity of the piezoelectric tactile sensor are analyzed.(4)3D force prediction of piezoelectric tactile sensor array based on BP neural network.Different forces are applied on the upper surface of the piezoelectric tactile sensor array.Based on the piezoelectric effect of PVDF piezoelectric film,the finite element analysis is carried out to calculate the voltage of the sensing element respectively.On this basis,the BP neural network was constructed based on the piezoelectric tactile sensor array model by using the approximation ability of BP neural network.The mapping relationship between the three-dimensional force applied on the sensor array surface and the voltage of the sensing unit was decoupled,and the accurate prediction of 3D force was realized.Based on the number of neurons in different hidden layers,several BP neural network models were built to determine the best number of neurons in the hidden layers and optimize the prediction results.In order to further reduce the error and improve the accuracy of 3D force prediction,the genetic algorithm(GA)is used to optimize the BP neural network to achieve the high precision prediction of 3D force applied on the surface of the piezoelectric tactile sensor array.
Keywords/Search Tags:piezoelectric tactile sensor, PVDF, piezoelectric effect, BP neural network, three-dimensional force prediction
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