Fault Diagnosis for Micro-Gas Turbine Engine Sensors via Wavelet Entropy

Sensors

Bing Yu¹  Dongdong Liu² 

[1] School of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;

关键词: fault diagnosis;    wavelet entropy;    wavelet decomposition;    gas turbine sensor;   

DOI  :  10.3390/s111009928

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.