Adaptive Threshold Algorithm Based on Autoregressive Model for Fault Detection of LRE in Ground Test

An adaptive threshold algorithm consisting of two stages based on autoregressive model was presented for monitoring the steady process of Liquid Propellant Rocket Engine(LRE) in ground test.For the first stage,the thresholds are calculated with the estimation values,standard deviation and band-width factors estimated by autoregressive model for steady parameter measurement values obtained from many different engine tests.Standard deviation and band-width factors which are trained by test data with the training algorithm are used at the beginning of the steady process of the engine test.For the second stage,the thresholds are calculated with the prediction values estimated using autoregressive model for steady parameter measurement mean values from many different engine tests.The standard deviation and band-width factors were used in the next steady process.The adaptive threshold algorithm based on autoregressive model was verified with the LRE ground test data.The results show that the approach can effectively and reliably monitor the LRE operation status.