应用反推神经网络检测液体火箭发动机多维故障

基于可测参数所构成的参数模式对应着一定的发动机故障模式，应用反推神经网络检测发动机多维故障，方法的有效性由只有泵效率下降和喷注器阻塞同时发生的数值仿真得到验证

LIQUID ROCKET ENGINE MULTI-FAILURE DETECTION USING BP NEURAL NETWORK

Based on a measurable survey pattern corresponding to a rocket engine failure pattern,the multi failure is detected by using back propagation (BP) neural network,which provides interesting means for pattern recognition and classification.The BP algorithm minimizes the mean square error between the desired and the actual output of the network.The learning algorithm is carried out with a gradient descent techniuqe.In order that the mean square error does not fall into partial minima noise,a sequence of random noises is recommended in the BP algorithm.As a test case,only the pump inefficiency and the sprayer jam in the liquid rocket engine were studied,and the failure detection simulation was given to show great advantages of the BP neural network.