In order to correct the test error caused by the dynamic characteristics of pressure sensor and avoid the influence of the error of sensor＇s dynamic model on compensation results,a dynamic compensation method of the ...In order to correct the test error caused by the dynamic characteristics of pressure sensor and avoid the influence of the error of sensor＇s dynamic model on compensation results,a dynamic compensation method of the pressure sensor is presented,which is based on quantum-behaved particle swarm optimization（QPSO）algorithm and the mean square error（MSE）.By using this method,the inverse model of the sensor is built and optimized and then the coefficients of the optimal compensator are got.This method is verified by the dynamic calibration with shock tube and the dynamic characteristics of the sensor before and after compensation are analyzed in time domain and frequency domain.The results show that the working bandwidth of the sensor is extended effectively.This method can reduce dynamic measuring error and improve test accuracy in actual measurement experiments.展开更多
The strain-rate dependent response of porcine skin oriented in the fiber direction is explored under tensile loading. Quasi-static response was obtained at strain rates in the range of 10-3s-1to 25 s-1. Characterizati...The strain-rate dependent response of porcine skin oriented in the fiber direction is explored under tensile loading. Quasi-static response was obtained at strain rates in the range of 10-3s-1to 25 s-1. Characterization of the response at even greater strain rates is accomplished by measuring the spatio-temporal evolution of the particle velocity and strain in a thin strip subjected to high speed impact loading that generates uniaxial stress conditions. These experiments indicate the formation of shock waves; the shock Hugoniot that relates particle velocity to the shock velocity and the dynamic stress to dynamic strain is obtained directly through experimental measurements, without any assumptions regarding the constitutive properties of the material.展开更多
基金The 11th Postgraduate Technology Innovation Project of North University of China(No.20141147)
文摘In order to correct the test error caused by the dynamic characteristics of pressure sensor and avoid the influence of the error of sensor＇s dynamic model on compensation results,a dynamic compensation method of the pressure sensor is presented,which is based on quantum-behaved particle swarm optimization（QPSO）algorithm and the mean square error（MSE）.By using this method,the inverse model of the sensor is built and optimized and then the coefficients of the optimal compensator are got.This method is verified by the dynamic calibration with shock tube and the dynamic characteristics of the sensor before and after compensation are analyzed in time domain and frequency domain.The results show that the working bandwidth of the sensor is extended effectively.This method can reduce dynamic measuring error and improve test accuracy in actual measurement experiments.
文摘The strain-rate dependent response of porcine skin oriented in the fiber direction is explored under tensile loading. Quasi-static response was obtained at strain rates in the range of 10-3s-1to 25 s-1. Characterization of the response at even greater strain rates is accomplished by measuring the spatio-temporal evolution of the particle velocity and strain in a thin strip subjected to high speed impact loading that generates uniaxial stress conditions. These experiments indicate the formation of shock waves; the shock Hugoniot that relates particle velocity to the shock velocity and the dynamic stress to dynamic strain is obtained directly through experimental measurements, without any assumptions regarding the constitutive properties of the material.
