固体火箭发动机内弹道多参数辨识及精准预示方法

Improving the prediction accuracy of the internal ballistic performance of solid rocket motor (SRM) plays an important role in enhancing the reliability of rockets and missiles operation.The internal ballistic performance was predicted by the com-binig the buring area inversely calculated by the measured pressure data of the motor with the measured burning rate of the grain, which still has large improvement in prediction accuracy.Aiming at this problem,a multi-parameter identification and prediction method for SRM internal ballistic was proposed.Based on the of limited measured data,the initial identification of burning rate coefficient,pressure index,propellant density and ablation rate coefficient of nozzle insert was carried out by GA (Genetic Algorithm).The model was updated on the basis of the inverse calculation burning area obtained by identification results.Then the secondary identification was carried out to modify the key parameters.Taking C1xb SRM in USA and a long passage SRM in China as examples,the internal ballistic performance in SRM was predicted. The calculation results show that the prediction results obtained by the method are in high agreement with the measured pressure data, which verifies the effectiveness of the method in improving the prediction accuracy of the internal ballistic performance.