Title :
Model-based diagnosis of gear fault under variable loading condition
Author :
Sang Hyuck Leem ; Joo-Ho Choi
Author_Institution :
Dept. of Aerosp. & Mech. Eng., Korea Aerosp. Univ., Goyang, South Korea
Abstract :
A model-based method is proposed to diagnose the gear fault in the gearbox under variable loading condition with the objective to apply it to the wind turbine CMS. A simple test bed is installed to illustrate the approach, which consists of motors and a pair of spur gears. A crack is imbedded at the tooth root of a gear. Tachometer-based order analysis, being independent on the shaft speed, is employed as a signal processing technique to identify the fault, which includes detecting the location and extracting the adequate feature. Lumped parameter dynamic model is used to simulate the operation of the test bed. In the model, the parameter related with the fault is inversely estimated by minimizing the difference between the simulated and measured features. Finally the parameter is used to estimate the crack size based on the regression model made by finite element stiffness analyses of a set of gears with imbedded crack. The results of estimated crack are validated by comparing with the actual ones of seeded crack.
Keywords :
condition monitoring; cracks; fault location; feature extraction; finite element analysis; gears; mechanical engineering computing; regression analysis; signal processing; tachometers; wind turbines; cracks; fault detection; fault extraction; fault identification; fault location; feature extraction; finite element stiffness analyses; gear fault model-based diagnosis; lumped parameter dynamic model; motors; regression model; shaft speed; signal processing technique; spur gears; tachometer-based order analysis; variable loading condition; wind turbine CMS; Estimation; Feature extraction; Gears; Load modeling; Shafts; Diagnosis; Fault severity assessment; Gear crack; Lumped parameter model; Order analysis; Variable loading condition; Wind turbine;
Conference_Titel :
Prognostics and Health Management (PHM), 2013 IEEE Conference on
Conference_Location :
Gaithersburg, MD
Print_ISBN :
978-1-4673-5722-7
DOI :
10.1109/ICPHM.2013.6621410