Method for analysis of the operation of a gas turbine
First Claim
1. A method of analyzing operation of a multistage compressor of a gas turbine including a plurality of compressor stages, wherein a neural network is trained based upon normal operation of the gas turbine, comprising:
- measuring a dynamic pressure signal by a pressure sensor in or on the multistage compressor;
measuring an operating parameter of the gas turbine by a further sensor during normal operation of the gas turbine;
performing a frequency analysis of the dynamic pressure signal, wherein a parameter of a frequency spectrum of the pressure signal is determined;
training a neural network based upon the measured operating parameter and the parameter of the frequency spectrum of the pressure signal,wherein the measured operating parameter and the parameter of the frequency spectrum of the pressure signal are input variables, andwherein a diagnosis characteristic value representing a probability measure of a presence of normal operation of the gas turbine as a function of the input variables is an output variable;
determining a characteristic frequency band based upon a rotation speed of the gas turbine and a number of guide vanes and rotor blades in the relevant compressor stage as a parameter of the frequency spectrum for each compressor stage; and
calculating for each characteristic frequency band an energy component of the pressure signal contained therein, the energy component being used as input variable for the neural network.
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Abstract
A method for analyzing the operation of a gas turbine is provided. A neural network based upon a normal operation of the gas turbine is learned. A dynamic pressure signal is read by a pressure sensor in or on the compressor of the turbine, and an operating parameter is read by a further sensor. The dynamic pressure signal is subjected to a frequency analysis, a parameter of a frequency spectrum of the pressure signal being determined. Based upon the measured operating parameter and the parameter of the frequency spectrum of the pressure signal, the neural network is learned. The measured operating parameter and the parameter of the frequency spectrum are input parameters, and a diagnostic characteristic value representing a probability of a presence of normal operation of the gas turbine as a function of the input parameters is output.
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Citations
20 Claims
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1. A method of analyzing operation of a multistage compressor of a gas turbine including a plurality of compressor stages, wherein a neural network is trained based upon normal operation of the gas turbine, comprising:
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measuring a dynamic pressure signal by a pressure sensor in or on the multistage compressor; measuring an operating parameter of the gas turbine by a further sensor during normal operation of the gas turbine; performing a frequency analysis of the dynamic pressure signal, wherein a parameter of a frequency spectrum of the pressure signal is determined; training a neural network based upon the measured operating parameter and the parameter of the frequency spectrum of the pressure signal, wherein the measured operating parameter and the parameter of the frequency spectrum of the pressure signal are input variables, and wherein a diagnosis characteristic value representing a probability measure of a presence of normal operation of the gas turbine as a function of the input variables is an output variable; determining a characteristic frequency band based upon a rotation speed of the gas turbine and a number of guide vanes and rotor blades in the relevant compressor stage as a parameter of the frequency spectrum for each compressor stage; and calculating for each characteristic frequency band an energy component of the pressure signal contained therein, the energy component being used as input variable for the neural network. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16)
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17. A method for monitoring a gas turbine, the method comprising:
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providing a neural network; measuring a dynamic pressure signal by a pressure sensor in or on a compressor of the gas turbine; measuring an operating parameter of the gas turbine by a further sensor during normal operation of the gas turbine; performing a frequency analysis of the dynamic pressure signal, wherein a parameter of a frequency spectrum of the pressure signal is determined; supplying the measured operating parameter and the parameter of the frequency spectrum of the pressure signal as input variables to the neural network; and outputting a diagnosis characteristic value as output variable from the neural network, wherein the neural network is trained based upon the measured operating parameter and the parameter of the frequency spectrum of the pressure signal such that a characteristic frequency band is determined based upon a rotation speed of the gas turbine and a number of guide vanes and rotor blades in the relevant compressor stage as a parameter of the frequency spectrum for each compressor stage, and an energy component of the dynamic pressure signal is calculated for each characteristic frequency band, wherein the energy component is used as input variable for the neural network. - View Dependent Claims (18)
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19. An apparatus for monitoring a gas turbine, comprising:
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a pressure sensor for measuring a dynamic pressure signal in or on a compressor of the gas turbine; a further sensor for measuring an operating parameter of the gas turbine during operation of the gas turbine; a frequency analysis device configured to perform a frequency analysis of the dynamic pressure signal, wherein, as a result, a parameter of a frequency spectrum of the pressure signal is determined; and a neural network, the measured operating parameter and the parameter of the frequency spectrum of the pressure signal being supplied to the neural network as input variables, wherein the neural network outputs a diagnosis characteristic value as output variable, wherein the neural network is trained based upon the measured operating parameter and the parameter of the frequency spectrum of the pressure signal such that a characteristic frequency band is determined based upon a rotation speed of the gas turbine and a number of guide vanes and rotor blades in the relevant compressor stage as a parameter of the frequency spectrum for each compressor stage, and an energy component of the dynamic pressure signal is calculated for each characteristic frequency band, wherein the energy component is used as input variable for the neural network. - View Dependent Claims (20)
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Specification