A Study on Crack Fault Diagnosis of Wind Turbine Simulation System

被引：0

作者：

Bae, Keun-Ho ^{[1
]}

Choi, Byung-Oh ^{[1
]}

Park, Jong-Won ^{[1
]}

Kim, Bong-Ki ^{[2
]}

机构：

[1] Korea Inst Machinery & Mat, Reliabil Assessment Ctr, Daejeon, South Korea

[2] Korea Inst Machinery & Mat, Acoust Grp, Daejeon, South Korea

来源：

PROCEEDINGS OF 2014 10TH INTERNATIONAL CONFERENCE ON RELIABILITY, MAINTAINABILITY AND SAFETY (ICRMS), VOLS I AND II | 2014年

关键词：

fault diagnosis; diagnostics; crack; wind-turbine; ANFIS; Support Vector Machine; SVM;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

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.

引用

页码：53 / 57

页数：5

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