DocumentCode :
3310091
Title :
Bladed disk crack detection through advanced analysis of blade time of arrival signal
Author :
Hanachi, H. ; Alavi, E. ; Liu, J. ; Banerjee, A. ; Koul, A. ; Liang, M.
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Carleton Univ., Ottawa, ON, Canada
fYear :
2012
fDate :
18-21 June 2012
Firstpage :
1
Lastpage :
4
Abstract :
Health condition monitoring and fault diagnostics of turbo fan engines play significant roles in overall cost reduction and reliability enhancement of the aircraft system. Among various types of potential faults in a turbo fan engine, crack initiation and propagation in the bladed disks of engines caused by high-cycle fatigue under cyclic loads are typical ones that could result in the breakdown of the engines if not detected at an early stage. Reliable fault detection techniques are therefore required to detect impending engine malfunctions as well as unexpected failures that could otherwise lead to costly and/or catastrophic consequences. Although a number of approaches have been reported in literature, it still remains very challenging to develop a reliable technique to accurately estimate the health condition of bladed disks of engines. As such, this paper presents a new technique for engine bladed disk crack detection through advanced analysis of blade time-of-arrival signal. Two stages of signal processing are involved in this technique: 1) signal preprocessing for removing the noise caused by rotor imbalance; and 2) signal post-processing for identifying the location of the crack. The effectiveness of the developed technique is validated experimentally in a spin rig test.
Keywords :
aerospace engineering; aerospace engines; blades; condition monitoring; cost reduction; fatigue cracks; fault diagnosis; mechanical engineering computing; rotors; signal denoising; aircraft system; blade time-of-arrival signal; bladed disk crack detection; cost reduction; crack initiation; crack location; crack propagation; cyclic load; fault diagnostics; health condition monitoring; high-cycle fatigue; noise removal; reliability enhancement; rotor imbalance; signal analysis; signal post-processing; signal processing; spin rig test; turbo fan engine; Blades; Engines; Feature extraction; Reliability; Shafts; Turbines; Vibrations; bladed disk; fault detection; feature extraction; physical modeling; signal processing; turbo fan engine; wavelet analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Prognostics and Health Management (PHM), 2012 IEEE Conference on
Conference_Location :
Denver, CO
Print_ISBN :
978-1-4673-0356-9
Type :
conf
DOI :
10.1109/ICPHM.2012.6299542
Filename :
6299542
Link To Document :
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