Neural network models for usage based remaining life computation

被引:9
|
作者
Parthasarathy, Girija [1 ]
Menon, Sunil [2 ]
Richardson, Kurt [2 ]
Jameel, Ahsan [2 ]
McNamee, Dawn [2 ]
Desper, Tori [2 ]
Gorelik, Michael [2 ]
Hickenbottom, Chris [2 ]
机构
[1] Honeywell Aerosp, Vehicle Hlth Management Lab, Minneapolis, MN 55418 USA
[2] Honeywell Aerosp, Phoenix, AZ 85034 USA
来源
JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME | 2008年 / 130卷 / 01期
关键词
D O I
10.1115/1.2771248
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
In engine structural life computations, it is common practice to assign a life of certain number of start-stop cycles based on a standard flight or mission. This is done during design through detailed calculations of stresses and temperatures for a standard flight, and the use of material property and failure models. The limitation of the design phase stress and temperature calculations is that they cannot take into account actual operating temperatures and stresses. This limitation results in either very conservative life estimates and subsequent wastage of good components or in catastrophic damage because of highly aggressive operational conditions, which were not accounted for in design. In order to improve significantly the accuracy of the life prediction, the component temperatures and stresses need to be computed for actual operating conditions. However thermal and stress models are very detailed and complex, and it could take on the order of a few hours to complete a stress and temperature simulation of critical components for a flight. The objective of this work is to develop dynamic neural network models that would enable us to compute the stresses and temperatures at critical locations, in orders of magnitude less computation time than required by more detailed thermal and stress models. The current paper describes the development of a neural network model and the temperature results achieved in comparison with the original models for Honeywell turbine and compressor components. Given certain inputs such as engine speed and gas temperatures for the flight, the models compute the component critical location temperatures for the same flight in a very small fraction of time it would take the original thermal model to compute.
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页数:7
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