Real-time simulation modeling method for variable geometric split axle type combustion gas turbine

A gas turbine, real-time simulation technology, applied in neural learning methods, design optimization/simulation, biological neural network models, etc., can solve problems such as difficulty in directly establishing simulation models, poor real-time performance of nonlinear models, and difficulty in ensuring simulation accuracy, to avoid Thermal calculation of working fluid, guarantee of simulation accuracy, and simplified establishment

Active Publication Date: 2017-06-20
INST OF ENGINEERING THERMOPHYSICS - CHINESE ACAD OF SCI
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Problems solved by technology

Especially for split-shaft gas turbines with variable geometry, such gas turbines include gas generators with adjustable guide vane compressors and power turbines. Due to the large number of variables, the nonlinear model established based on the working mechanism of the gas turbine has poor real-time performance.
Although the linearized modeling method has good real-time performance, it is dif

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  • Real-time simulation modeling method for variable geometric split axle type combustion gas turbine
  • Real-time simulation modeling method for variable geometric split axle type combustion gas turbine

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[0030] In order to make the object, technical solution and advantages of the present invention clearer, the following describes the present invention in further detail with reference to the accompanying drawings and examples, so that the advantages and features of the present invention can be more easily understood by those skilled in the art. It should be noted that the following descriptions are only preferred embodiments of the present invention, and therefore do not limit the protection scope of the present invention. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the scope or spirit of the invention. For example, features illustrated or described as part of one embodiment can be used with another embodiment to yield a still further embodiment. Therefore, it is intended that the present invention cover such modifications and variations as come within the scope of...

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Abstract

The invention relates to a real-time simulation modeling method for a variable geometric split axle type combustion gas turbine. The combustion gas turbine suitable for the method has the structure characteristics of adjustable compressor guide vane and split form and is composed of a fuel gas generator and a power turbine. The method comprises the following steps: selecting a sample point; acquiring a training sample point; utilizing the acquired sample point to train a RBF neural network; utilizing a part modeling method to establish a power turbine calculating module; connecting the module with the RBF neural network, wherein the RBF neural network is responsible for outputting the related parameters of the fuel gas generator and the power turbine calculating module is responsible for outputting the related parameters, such as, power, thereby acquiring a real-time simulation model of the combustion gas turbine. According to the modeling method for a real-time simulation model provided by the invention, the condition of angle variation of an entry guide vane of the air compressor is considered, the model is reasonably simplified, the advantages of the RBF neural network and the module method are combined with each other, the high instantaneity and high precision of the model are guaranteed while the sample size is greatly reduced.

Description

technical field [0001] The invention relates to the field of gas turbines, in particular to a modeling method for real-time simulation of variable geometry split-shaft gas turbines. Background technique [0002] In the process of gas turbine semi-physical simulation experiments and gas turbine control law research, the real-time performance of the gas turbine simulation model is high. Especially for split-shaft gas turbines with variable geometry, such gas turbines include gas generators with adjustable vane compressors and power turbines. Due to the large number of variables, the nonlinear model established based on the working mechanism of gas turbines has poor real-time performance. Although the linearized modeling method has better real-time performance, it is difficult to guarantee the simulation accuracy for the situation far away from the steady-state working condition. Although the neural network-based system identification method can achieve high accuracy and real-...

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Application Information

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IPC IPC(8): G06F17/50G06N3/08
CPCG06F30/20G06N3/08
Inventor 尹钊田拥胜王涛张华良曾德堂高庆谭春青
Owner INST OF ENGINEERING THERMOPHYSICS - CHINESE ACAD OF SCI
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