Research On Dynamic Compensation Of Piezoresistive Sensor Based On Improved Fruit-fly Optimization Algorithm

Shock wave will affect the operator's health and damage the peripheral equipment of weapon.It is very important to obtain the parameters of the shock wave in the gun and other weapon stereotyping test.As a kind of transient signal,shock wave signal has the characteristics of fast propagation speed,wide range and wide dynamic range of signal amplitude,which requires very high dynamic performance of the test system.However,as the core component of the test system,the insufficient dynamic characteristics of the sensor make it inevitable to introduce a large number of errors in the testing process.In order to reduce the sensor test error,the sensor dynamic compensation system is constructed based on the group intelligence algorithm and the transfer model of the independent sensor system,and the transfer function of the compensation system is obtained directly.The Drosophila optimization algorithm(FOA)is introduced and improved,and then it is combined with the sensor dynamic compensation technology to carry on the research.In order to solve the problem that the original Fruit-fly optimization algorithm's taste concentration cannot be negative,the candidate solution can be generated directly by using the individual spatial information of Fruit-fly,so that the search solution space of the improved algorithm can contain the negative definition domain.The strategy of dynamic adjustment of search step size is introduced to enhance the optimization performance of the algorithm.Five typical high-dimensional complex functions were used to test the optimization ability of Particle Swarm optimization algorithm,Fruit-fly optimization algorithm and improved Fruit-fly optimization algorithm.The comparison of the test results shows that the search accuracy and efficiency of the DFOA algorithm are improved,and the application range is extended,which proves that the improvement of the Fruit-fly optimization algorithm is effective.The improved Fruit-fly optimization algorithm is applied to sensor dynamic compensation.Firstly,the optimal dynamic compensation system for the sensor is obtained by using the shock tube calibration data of the sensor and combining with the DFOA algorithm.The dynamic compensation system reduces the output signal overshoot of the sensor from 130% to 3%,and increases the rise time to 11.5?s.Finally,the built dynamic compensation system is applied to test the measured shock wave signal.The experimental results show that the original shock wave signal can be recovered from the high resonance data,and the important shock wave parameters are obtained.It is proved that the dynamic compensation system based on DFOA algorithm can effectively improve the dynamic performance and test accuracy of the sensor.