Gas path fault diagnostic method for marine gas turbine based on fuzzy Petri net (FPN)

A technology for gas turbine and fault diagnosis, which is used in gas turbine engine testing, jet engine testing, biological neural network models, etc.

Inactive Publication Date: 2011-09-07
NAVAL UNIV OF ENG PLA
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Problems solved by technology

[0009] In order to effectively overcome the problems caused by fuzzy and uncertain factors in the gas path fault diagnosis of marine gas turbines, and in order to fully reflect the ignition rules of FPN, the present invention proposes a FPN model for the characteristics o

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  • Gas path fault diagnostic method for marine gas turbine based on fuzzy Petri net (FPN)
  • Gas path fault diagnostic method for marine gas turbine based on fuzzy Petri net (FPN)

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[0039] The specific implementation manners of the present invention will be described in detail below in conjunction with the accompanying drawings, but they do not constitute a limitation of the present invention, and are only examples. At the same time, the advantages of the present invention will become clearer and easier to understand.

[0040] The main neural network model is composed of multiple sub-neural network modules. Environmental and operating parameters such as atmospheric temperature, atmospheric pressure, and throttle position are the input parameters of each subnetwork; operating parameters such as low-pressure compressor speed, high-pressure compressor speed, power turbine speed, high-pressure compressor outlet pressure, and low-pressure turbine outlet average temperature is the output parameter of each subnet.

[0041] The present invention is based on the marine gas turbine gas path fault diagnosis method of fuzzy Petri net, and it comprises the steps:

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Abstract

The invention discloses a gas path fault diagnostic method for a marine gas turbine based on a fuzzy Petri net (FPN), comprising the following steps of: (1) obtaining the operating standard value of the marine gas turbine; (2) based on an actually-measured value, calculating the membership grade of the actual operating parameter deviation belonging to the criterion deviation fuzzy subset by using a membership function; (3) defining the FPN in response to the characteristics of the fault diagnostic Petri net after determining the operating standard value and the deviation; and (4) determining a FPN reasoning algorithm for gas path fault diagnosis for the marine gas turbine based on related definitions of the transitional enabling and igniting rules. Through the gas path fault diagnostic method for the marine gas turbine based on the fuzzy Petri net (FPN), the defects of not strong university, wrong judgment and reasoning of the traditional method are overcome; it is actually proved that the problems of fuzziness and nondeterminacy in an gas path fault can be effectively solved by the gas path fault diagnostic algorithm for the marine gas turbine established by the gas path fault diagnostic method disclosed by the invention.

Description

technical field [0001] The invention belongs to a performance diagnosis and trend analysis system of a marine gas turbine, in particular to a method for diagnosing a gas path fault of a marine gas turbine based on a fuzzy Petri net. Background technique [0002] The gas circuit fault diagnosis of gas turbine is to compare the measurable parameters of the gas circuit in the actual operation of the engine (such as: speed, pressure, temperature, etc.) with the reference value of normal operation, and the resulting deviation is used as the basis for detection, isolation and identification of component failure method. The principle of this diagnostic method was first proposed by Urban in 1972. The traditional gas circuit fault diagnosis uses the deviation criterion of deterministic theory, that is, when a set of parameter deviations is a set of fixed values, it may represent a certain fault, but There is actually a lot of uncertainty and ambiguity in this judgment. [0003] Fir...

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Application Information

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IPC IPC(8): G01M15/14G06N3/02
Inventor 刘永葆姜荣俊余又红马良荔高建华
Owner NAVAL UNIV OF ENG PLA
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