Gas turbine system performance prediction method based on key component failure model

A technology for gas turbines and prediction methods, which is applied in computing models, machine learning, special data processing applications, etc., can solve the problem that gray models cannot be used for long-term prediction, etc., and achieves the effect of high matching degree

Active Publication Date: 2018-04-20
CSSC SYST ENG RES INST
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Problems solved by technology

There is a problem that the gray model cannot make long-term predictions

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  • Gas turbine system performance prediction method based on key component failure model
  • Gas turbine system performance prediction method based on key component failure model
  • Gas turbine system performance prediction method based on key component failure model

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Embodiment Construction

[0052]Preferred embodiments of the present invention will be specifically described below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of the application and are used together with the embodiments of the present invention to explain the principle of the present invention.

[0053] A specific embodiment of the present invention discloses a method for predicting the performance of a gas turbine system based on a key component failure model. The method utilizes the performance decline trend of key components of the gas turbine system to predict the overall performance decline trend of the gas turbine system, such as figure 1 shown, including the following steps:

[0054] Step S1. Based on the structure and functional characteristics of the gas turbine system, perform a three-level decomposition of the gas turbine system, and decompose the gas turbine system into three levels: subsystems, key equipment, and key components

[00...

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Abstract

The invention relates to a gas turbine system performance prediction method based on a key component failure model. The method comprises the following steps of layering a gas turbine system; utilizingan analytic hierarchy process to carry out influence weight analysis from the component to the system; obtaining the reliability change tendency of the key component; and according to the reliabilityanalysis result of the key component, utilizing a weight coefficient, which is obtained in the hierarchical analysis, between the component and the system to calculate the reliability change tendencyof the whole gas turbine system. By use of the method, the gas turbine system is layered to construct a weight influence matrix, a foundation for carrying out performance prediction from the component to the system is laid, life cycle data is used for carrying out the prediction of a key component performance degradation trend, each key component and the system are subjected to related quantification processing, and the future performance change trend of the whole system is obtained through the degradation performance prediction result of the key component.

Description

technical field [0001] The invention relates to the field of electromechanical technology, in particular to a gas turbine system performance prediction method based on a key component failure model. Background technique [0002] Due to the complex structure of the gas turbine system, various changes in working conditions, and mutual coupling and influence of various components, the gas turbine system often fails. At the same time, as one of the main propulsion systems of the ship, a failure of the gas turbine system will not only cause the ship to be forced to stop sailing, but also affect navigation. efficiency, and will bring high maintenance costs, and even lead to safety accidents. Therefore, the research on the performance prediction technology of the ship gas turbine system is very important to reduce the failure rate and ensure the normal navigation of the ship. [0003] Traditional performance prediction methods often take a certain component as the research object,...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N99/00
CPCG06N20/00G06F30/20
Inventor 蒋云鹏邱伯华何晓刘学良魏慕恒
Owner CSSC SYST ENG RES INST
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