Abstract
Sensor fault diagnosis is necessary to ensure the normal operation of a gas turbine system. However, the existing methods require too many resources and this need can’t be satisfied in some occasions. Since the sensor readings are directly affected by sensor state, sensor fault diagnosis can be performed by extracting features of the measured signals. This paper proposes a novel fault diagnosis method for sensors based on wavelet entropy. Based on the wavelet theory, wavelet decomposition is utilized to decompose the signal in different scales. Then the instantaneous wavelet energy entropy (IWEE) and instantaneous wavelet singular entropy (IWSE) are defined based on the previous wavelet entropy theory. Subsequently, a fault diagnosis method for gas turbine sensors is proposed based on the results of a numerically simulated example. Then, experiments on this method are carried out on a real micro gas turbine engine. In the experiment, four types of faults with different magnitudes are presented. The experimental results show that the proposed method for sensor fault diagnosis is efficient.
Highlights
Gas turbines are one of the most important types of power equipment, widely used in modern aircraft propulsion systems and power systems
This paper proposes a fault diagnosis method for micro-gas turbine sensors operating under nonstationary conditions
The discrete wavelet transform (DWT) of signal can be obtained through Equation (4)
Summary
Gas turbines are one of the most important types of power equipment, widely used in modern aircraft propulsion systems and power systems. The control and monitoring of gas turbine systems depend on accurate and reliable sensor readings from a considerable number of sensors. Botros et al [2] proposed an application of radial basis function neural networks for sensor fault detection on an RB211 gas turbine driven compressor station. Romesis et al [6] presented a sensor fault detection method based on a probabilistic neural network. It is hard to determine when a particular fault takes place To improve this deficiency, Gabor proposed the short-time Fourier transform (STFT) [10]. This paper proposes a fault diagnosis method for micro-gas turbine sensors operating under nonstationary conditions. A fault diagnosis method for gas turbine sensors is proposed based on the numerically simulated example. Experiments are carried out on this method, and the results show that it is efficient
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