scholarly journals A step parameters prediction model based on transfer process neural network for exhaust gas temperature estimation after washing aero-engines

2021 ◽  
Author(s):  
Zhiqi YAN ◽  
Shisheng ZHONG ◽  
Lin LIN ◽  
Zhiquan CUI ◽  
Minghang ZHAO
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Transfer Process ◽  
Exhaust Gas ◽  
Gas Temperature ◽  
Temperature Estimation ◽  
Model Based ◽  
Aero Engines ◽  
Exhaust Gas Temperature ◽  
Step Parameters

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

Aeroengine Exhaust Gas Temperature Prediction Using Process Neural Network with Time-Varying Threshold Functions

2013 ◽  
Vol 423-426 ◽  
pp. 2341-2346
Author(s):  
Gang Ding ◽  
Xiong Wei Wang ◽  
Da Lei
Keyword(s):  
Neural Network ◽  
Neural Network Model ◽  
Orthogonal Basis ◽  
Basis Functions ◽  
Exhaust Gas ◽  
Time Varying ◽  
Gas Temperature ◽  
Threshold Functions ◽  
Exhaust Gas Temperature ◽  
Threshold Process

To predict the aeroengine exhaust gas temperature (EGT) more precisely, a process neuron with time-varying threshold function is proposed in this paper, and then the time-varying threshold process neural network model comprised of the presented process neurons is used for EGT prediction. By introducing a group of appropriate orthogonal basis functions, the input functions, the weight functions and the threshold functions of the time-varying threshold process neural network can be expanded as linear combinations of the given orthogonal basis functions, thus to eliminate the integration operation, then to simplify the time aggregation operation. The corresponding learning algorithm is also presented, and the effectiveness of the time-varying threshold process neural network model is evaluated through the prediction of EGT series from practical aeroengine condition monitoring.

Lime kiln conversion from coke to natural gas operation – an option in direction of sustainable energy

2020 ◽  
pp. 431-434
Author(s):  
Oliver Arndt
Keyword(s):  
Natural Gas ◽  
New Technology ◽  
Exhaust Gas ◽  
Gas Temperature ◽  
Gaseous Fuels ◽  
Lime Kiln ◽  
Lime Kilns ◽  
Co2 Balance ◽  
Exhaust Gas Temperature

This paper deals with the conversion of coke fired lime kilns to gas and the conclusions drawn from the completed projects. The paper presents (1) the decision process associated with the adoption of the new technology, (2) the necessary steps of the conversion, (3) the experiences and issues which occurred during the first campaign, (4) the impacts on the beet sugar factory (i.e. on the CO2 balance and exhaust gas temperature), (5) the long term impressions and capabilities of several campaigns of operation, (6) the details of available technologies and (7) additional benefits that would justify a conversion from coke to natural gas operation on existing lime kilns. (8) Forecast view to develop systems usable for alternative gaseous fuels (e.g. biogas).

scholarly journals Exhaust Gas Temperature Measurements in Diagnostics of Turbocharged Marine Internal Combustion Engines Part I Standard Measurements

2015 ◽  
Vol 22 (1) ◽  
pp. 47-54 ◽  
Author(s):  
Zbigniew Korczewski
Keyword(s):  
Internal Combustion Engines ◽  
Internal Combustion ◽  
Technical Condition ◽  
Temperature Measurements ◽  
Injection System ◽  
Exhaust Gas ◽  
Combustion Engines ◽  
Gas Temperature ◽  
Measuring Signal ◽  
Exhaust Gas Temperature

Abstract The article discusses the problem of diagnostic informativeness of exhaust gas temperature measurements in turbocharged marine internal combustion engines. Theoretical principles of the process of exhaust gas flow in turbocharger inlet channels are analysed in its dynamic and energetic aspects. Diagnostic parameters are defined which enable to formulate general evaluation of technical condition of the engine based on standard online measurements of the exhaust gas temperature. A proposal is made to extend the parametric methods of diagnosing workspaces in turbocharged marine engines by analysing time-histories of enthalpy changes of the exhaust gas flowing to the turbocompressor turbine. Such a time-history can be worked out based on dynamic measurements of the exhaust gas temperature, performed using a specially designed sheathed thermocouple. The first part of the article discusses possibilities to perform diagnostic inference about technical condition of a marine engine with pulse turbocharging system based on standard measurements of exhaust gas temperature in characteristic control cross-sections of its thermal and flow system. Selected metrological issues of online exhaust gas temperature measurements in those engines are discusses in detail, with special attention being focused on the observed disturbances and thermodynamic interpretation of the recorded measuring signal. Diagnostic informativeness of the exhaust gas temperature measurements performed in steady-state conditions of engine operation is analysed in the context of possible evaluations of technical condition of the engine workspaces, the injection system, and the fuel delivery process.

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