Aero-Engine Exhaust Gas Temperature Prognostic Model Based on Gated Recurrent Unit Network

2018 ◽  
Author(s):  
Shisheng Zhong ◽  
Zhen Li ◽  
Lin Lin ◽  
Yongjian Zhang
Keyword(s):  
Prognostic Model ◽  
Exhaust Gas ◽  
Gas Temperature ◽  
Engine Exhaust ◽  
Model Based ◽  
Aero Engine ◽  
Exhaust Gas Temperature ◽  
Gated Recurrent Unit ◽  
Unit Network

Application of the Regularization Chaos Prediction Model in Aero-Engine Performance Parameters

2012 ◽  
Vol 424-425 ◽  
pp. 347-351 ◽  
Author(s):  
Yong Sheng Shi ◽  
Jun Jie Yue ◽  
Yun Xue Song
Keyword(s):  
Prediction Model ◽  
Simulation Analysis ◽  
Search Algorithm ◽  
Engine Performance ◽  
Forecasting Model ◽  
Exhaust Gas ◽  
Gas Temperature ◽  
Engine Exhaust ◽  
Aero Engine ◽  
Exhaust Gas Temperature

Based on the research of complexity and non-linearity of aero-engine exhaust gas temperature (EGT) system, a regularization chaotic prediction model was proposed to build short time forecasting model of EGT. In this paper, in order to gain the best parameter to improve the accuracy of the forecasting model, a simple search algorithm arithmetic was adopted. The simulation analysis shows that the proposed forecasting model obviously exceeded the traditional chaotic forecasting model on prediction accuracy. Therefore, this arithmetic is efficient and feasible for a short-term prediction of aero-engine exhaust gas temperature

scholarly journals Aero-engine exhaust gas temperature prediction based on LightGBM optimized by improved bat algorithm

2020 ◽  
pp. 246-246
Author(s):  
Dingzhe Li ◽  
Jingbo Peng ◽  
Dawei He
Keyword(s):  
Goodness Of Fit ◽  
Bat Algorithm ◽  
Percentage Error ◽  
Exhaust Gas ◽  
Gas Temperature ◽  
Engine Exhaust ◽  
Data Set ◽  
Aero Engine ◽  
The Mean ◽  
Exhaust Gas Temperature

In this paper, an aero-engine exhaust gas temperature (EGT) prediction model based on LightGBM optimized by the chaotic rate bat algorithm (CRBA) is proposed to monitor aero-engine performance effectively. By introducing chaotic rate, the convergence speed and precision of bat algorithm are im-proved, which CRBA is obtained. LightGBM is optimized by CRBA and it is used to predict EGT. Taking a type of aero-engine for example, some relevant performance parameters from the flight data measured by airborne sensors were selected as input variables and EGT as output variables. The data set is divided into training and test sets, and the CRBA-LightGBM model is trained and tested, and compared with ensemble algorithms such as RF, XGBoost, GBDT, LightGBM and BA-LightGBM. The results show that the mean absolute error (MAE) of this method in the prediction of EGT (after normalization) is 0.0065, the mean absolute percentage error (MAPE) is 0.77% and goodness of fit R2 has reached to 0.9469. The prediction effect of CRBA-LightGBM is better than other comparison algorithms and it is suitable for aero-engine condition monitoring.

A Parametric Study of Diesel Oxidation Catalyst Performance on CO Reduction in Diesel Dual Fuel Engine Exhaust

2015 ◽  
Vol 656-657 ◽  
pp. 538-543 ◽  
Author(s):  
Sirichai Jirawongnuson ◽  
Worathep Wachirapan ◽  
Tul Suthiprasert ◽  
Ekathai Wirojsakunchai
Keyword(s):  
Diesel Oxidation Catalyst ◽  
Oxidation Catalyst ◽  
Dual Fuel ◽  
Exhaust Gas ◽  
Gas Temperature ◽  
Engine Exhaust ◽  
Gas System ◽  
Diesel Oxidation ◽  
Co Reduction ◽  
Exhaust Gas Temperature

In this research study, a synthetic exhaust gas system is employed to simulate various exhaust conditions similar to those from conventional diesel and Dual Fuel-Premixed Charge Compression Ignition (DF-PCCI) combustion. OEM DOC is tested to compare the effectiveness of reducing CO from both exhaust characteristics. Variations of the temperature and the concentration of CO, THC, and O2 are done to investigate DOC performance on CO reductions according to Design of Experiment (DOE) concept. The results showed that in DF-PCCI exhaust conditions, DOC requires higher exhaust gas temperature as well as O2 concentration to reduce CO emissions.

scholarly journals Signal filtering method of the fast-varying diesel exhaust gas temperature

2018 ◽  
Vol 175 (4) ◽  
pp. 48-52
Author(s):  
Patrycja PUZDROWSKA
Keyword(s):  
Diesel Exhaust ◽  
Exhaust Gas ◽  
Gas Temperature ◽  
Engine Exhaust ◽  
Temperature Changes ◽  
Filtering Method ◽  
Significant Parameter ◽  
Mathematical Processing ◽  
Exhaust Gas Temperature ◽  
The Impact

The paper presents the problem of the impact of external distortions originating on laboratory test stands on the results of measurements of fast-varying diesel exhaust gas temperature. It has been stressed how significant the aspect of the test stand adaptation is during an experiment to ensure the smallest possible impact. This paper, however, focuses on the methods of mathematical processing of a signal recorded during experimental research of a real object. The most significant parameter requiring filtering is the fast-varying exhaust gas temperature in the engine exhaust channel. Methods of mathematical processing adequate to this type of distorted signal have been presented, particularly those that can be used in the Matlab environment and consisting in averaging of the obtained curves of temperature changes. The results of the application of these methods have also been presented on actual curves recorded during laboratory tests and their evaluation has been made.

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