Title :
A study on crack fault diagnosis of wind turbine simulation system
Author :
Keun-Ho Bae ; Byung-Oh Choi ; Jong-Won Park ; Bong-Ki Kim
Author_Institution :
Reliability Assessment Center, Korea Inst. of Machinery & Mater., Daejeon, South Korea
Abstract :
An experimental gear-box was set-up to simulate the real situation of the wind-turbine. Artificial cracks of different sizes were machined into the gear. Vibration signals were acquired to diagnose the different crack fault conditions. Time-domain features such as root mean square, variance, kurtosis, normalized 6th central moments were used to capture the characteristics of different crack conditions. Normal condition, 1 mm crack condition, 2mm crack condition, 6mm crack condition, and tooth fault condition were compared using ANFIS and DAG-SVM methods, and three different DAG-SVM models were compared. High-pass filtering improved the success rates remarkably in the case of DAG-SVM.
Keywords :
condition monitoring; crack detection; fault diagnosis; filtering theory; gears; inference mechanisms; mean square error methods; mechanical engineering computing; statistical analysis; support vector machines; vibrations; wind turbines; ANFIS; DAG-SVM models; adaptive networked-based fuzzy inference system; crack fault conditions; crack fault diagnosis; gearbox; high-pass filtering; kurtosis; normalized 6th central moments; root mean square method; time-domain features; variance analysis; vibration signals; wind turbine simulation system; Condition monitoring; Fault diagnosis; Fuzzy logic; Gears; Root mean square; Support vector machines; Wind turbines; ANFIS; SVM; Support Vector Machine; crack; diagnostics; fault diagnosis; wind-turbine;
Conference_Titel :
Reliability, Maintainability and Safety (ICRMS), 2014 International Conference on
Print_ISBN :
978-1-4799-6631-8
DOI :
10.1109/ICRMS.2014.7107135
