Exhaust gas temperature data prediction by autoregressive models
作者： Amar Kumar , Alka Srivastava , Nita Goel , Jon McMaster
DOI: 10.1109/CCECE.2015.7129408
关键词:
摘要: Gas turbine engine performance and health conditions are continuously assessed by exhaust gas temperature that indicate the thermal condition of engine. Analysis (EGT) data its prediction is very important for operational safety, reliability, life cycle cost power output. Autoregressive (AR) moving average (MA) techniques, either singly or in combination used modeling, validation EGT this work. Model investigated estimating percent error mean squared error. Models short long term predictions. models with small indices found to offer best performance.
sci-hub.se 参考文章(18)
David Clifton, Condition Monitoring of Gas-Turbine Engines ,(2006)
G. E. P. Box, D. R. Cox, An Analysis of Transformations Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 26, pp. 211- 243 ,(1964) , 10.1111/J.2517-6161.1964.TB00553.X
Magnus Fast, Artificial Neural Networks for Gas Turbine Monitoring ,(2010)
Amar Kumar, Avisekh Banerjee, Alka Srivastava, Nita Goel, Prediction of exhaust gas temperature in GTE by multivariate regression analysis and anomaly detection canadian conference on electrical and computer engineering. pp. 1- 6 ,(2014) , 10.1109/CCECE.2014.6901166
G. E. P. Box, G. C. Tiao, Intervention Analysis with Applications to Economic and Environmental Problems Journal of the American Statistical Association. ,vol. 70, pp. 70- 79 ,(1975) , 10.1080/01621459.1975.10480264
Rob J. Hyndman, Anne B. Koehler, Another look at measures of forecast accuracy International Journal of Forecasting. ,vol. 22, pp. 679- 688 ,(2006) , 10.1016/J.IJFORECAST.2006.03.001
George E.P. Box, D. A. Pierce, Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models Journal of the American Statistical Association. ,vol. 65, pp. 1509- 1526 ,(1970) , 10.2307/2284333
Amar Kumar, Avisekh Banerjee, Alka Srivastava, Nita Goel, Alok Goel, Gas turbine engine operational data analysis for anomaly detection: Statistical vs. neural network approach canadian conference on electrical and computer engineering. pp. 1- 5 ,(2013) , 10.1109/CCECE.2013.6567813
ROBERT KOHN, CRAIG F. ANSLEY, Efficient estimation and prediction in time series regression models Biometrika. ,vol. 72, pp. 694- 697 ,(1985) , 10.1093/BIOMET/72.3.694
G. M. LJUNG, G. E. P. BOX, On a measure of lack of fit in time series models Biometrika. ,vol. 65, pp. 297- 303 ,(1978) , 10.1093/BIOMET/65.2.297