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Fault Diagnosis for Micro-Gas Turbine Engine Sensors via Wavelet Entropy
School of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
* Author to whom correspondence should be addressed.
Received: 21 September 2011; in revised form: 13 October 2011 / Accepted: 18 October 2011 / Published: 21 October 2011
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.
Keywords: fault diagnosis; wavelet entropy; wavelet decomposition; gas turbine sensor
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MDPI and ACS Style
Yu, B.; Liu, D.; Zhang, T. Fault Diagnosis for Micro-Gas Turbine Engine Sensors via Wavelet Entropy. Sensors 2011, 11, 9928-9941.
Yu B, Liu D, Zhang T. Fault Diagnosis for Micro-Gas Turbine Engine Sensors via Wavelet Entropy. Sensors. 2011; 11(10):9928-9941.
Yu, Bing; Liu, Dongdong; Zhang, Tianhong. 2011. "Fault Diagnosis for Micro-Gas Turbine Engine Sensors via Wavelet Entropy." Sensors 11, no. 10: 9928-9941.