1. Prediction of Ship Main Engine Exhaust Gas Temperature Using AR Model
- Author
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Peng Zhang, Yue Wen Zhang, Yong Jiu Zou, and Zhu Feng Liu
- Subjects
Trend analysis ,Engineering ,Autoregressive model ,Meteorology ,Power station ,business.industry ,Approximation error ,Thermal ,Exhaust gas ,General Medicine ,Time series ,business ,Automotive engineering - Abstract
In order to forecast the malfunctional state of main power plant on ships through predicting the trend of unsteadily changed thermal performance parameters in main power plant system, this paper established AR model for thermal performance parameters using time series analysis method, by which to predict the change trend analysis of thermal performance parameters, and comparing the predicted values and the measured values. The actual application case of predicting a main engine’s exhaust temperature has been validated by using of the AR model, and results showed that: AR model can accurately predict the change trend of smoke temperature, and the prediction precision is higher, the average relative error was 0.25%.
- Published
- 2014
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