Research On Dynamic Characteristics Of Transient Temperature Measurement System

During the firing process of artillery and other weapons,the high-temperature and high-pressure gunpowder gas inside the body tube quickly scours the inner bore wall of the weapon body tube,causing the inner bore wall of the weapon body tube to generate transient high temperature.The transient high temperature not only melts the metal layer on the surface of the gun barrel and accelerates the ablation of the gun barrel,which seriously affects the service life of the barrel,but also causes the bending deformation of the barrel to reduce the shooting rate of the weapon.During the temperature test of the weapon body tube,a thermocouple test system is usually used,but due to the thermal inertia and limited heat conduction of the thermocouple test system,the response speed of the thermocouple test system cannot keep up with the temperature change rate,and the measurement results have errors.In order to improve the dynamic characteristics of the thermocouple test system and reduce the measurement error,this thesis introduces an improved gray wolf optimization algorithm(IGWO),which uses this algorithm to directly obtain the transfer function of the compensation system,thereby constructing a better thermocouple dynamic compensation system.The main research contents are as follows:(1)For the original gray wolf optimization algorithm,when solving complex optimization problems,as the number of iterations increases and the number of dimensions increases,the diversity of the internal population of the algorithm decreases,which makes the algorithm in the process of optimization.There is a problem of slow convergence and easy fall into local extremes.To this end,this thesis introduces dynamic weighting factors and improved candidate solution generation strategies into the gray wolf optimization algorithm,thereby enhancing the algorithm's optimization capabilities.Through the optimization of five typical high-dimensional complex test functions,the test results show that the optimization accuracy of the IGWO algorithm is stronger than the original gray wolf algorithm and particle swarm algorithm,which proves the effectiveness of the improvement of the gray wolf optimization algorithm.(2)The improved gray wolf optimization algorithm is applied to the dynamic compensation of thermocouple sensors.Firstly,an optimal dynamic compensation system was constructed based on the data measured by the thermocouple sensor in the water bath method experiment and the IGWO algorithm.This dynamic compensation system can increase the time constant of the thermocouple from 0.0685 s to 0.0147 s,and its dynamic error by almost 75%.Finally,the system was applied to the measured flame data.The experimental results show that the flame temperature measured by the system is closer to the real flame temperature value,which proves that the compensation system obtained by the IGWO algorithm can effectively improve the thermocouple dynamics.Performance,reduce the dynamic error introduced during thermocouple measurement,and improve compensation accuracy.