基于自回归模型的RBCC隔离段激波串位置识别与压力值预估

In order to clearly and objectively identify the location of the shock train in the isolator of the Rocket-based combined-cycle (RBCC), the measured pressure data of the RBCC isolator in the direct connection test under Ma=6, 4, 3.5 conditions were arranged according to the order of time to form a time series, Auto-Regressive (AR) model was established and the data of Akaike information criterion (AIC) was calculated. The location of the shock train was identified under different working conditions. The results show that when the pressure measurement point of the isolator is not affected by the shock train, the real-time pressure only fluctuates slightly, and the AIC changes steadily. When the shock train moves to the pressure measurement point, the pressure at the point increases, the oscillation amplitude increases obviously, then the AIC increases instantaneously. The position where the first AIC of the measurement point along the engine increases by more than 500 in the same time period and maintains a larger value without changing the test condition is the location of the shock train. Compared with the pressure ratio method, the time series analysis method can sensitively monitor the rise and oscillation of the pressure, the shock train leading edge location identification is more accurate. The Auto-Regressive model can also be used to predict the internal pressure of the shock train. The pressure data of the measurement point under Ma=6, 4, 3.5 conditions within 160 ms were taken, and the sampling frequency was 1 kHz. The Auto-Regressive model is established using the first 80 ms data, and the pressure prediction and accuracy test of the last 80 ms are completed. The average error of prediction under the three working conditions is 3.21%, 7.68% and 6.49%, respectively.