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.
Based on LabVlEW platform, a distributed dynamic storage testing system is designed for measuring transient high temperature signals of explosion field. Using a highpower semiconductor laser as heat source, a traceable dynamic calibration system is established to perform dynamic calibration of thermocouples. With quantumbehaved particle swam optimization （QP-SO） algorithm on MATLAB platform, a model of dynamic compensation filter is established. It is used by LabVIEW that calls MATLAB Script nodes or COM components to accomplish the mixed programming of LabVIEW and MATLAB, further to compensate the temperature values of the thermocouples dynamically. The experimental results show that the technique that combines temperature measurement system with LabVIEW platform is applied well in testing the explosion temperature of ther mobaric weaponry and makes the compensation values closer to the actual signals.
