High Performance Remaining Useful Life Prediction for Gearbox

被引：0

作者：

Ayhan, Bulent ^{[1
]}

Kwan, Chiman ^{[1
]}

Liang, Steven Y. ^{[2
]}

机构：

[1] Signal Proc Inc, Rockville, MD 20850 USA

[2] Georgia Tech, Atlanta, GA USA

来源：

2018 IEEE INTERNATIONAL CONFERENCE ON PROGNOSTICS AND HEALTH MANAGEMENT (ICPHM) | 2018年

关键词：

gearbox; prognostics; remaining useful life prediction; PHM; damage curve approach; FAULT DIAGNOSTICS; SENSOR;

D O I：

暂无

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

Gearbox failure prediction is important for many applications. We present four approaches for predicting the remaining useful life of gearboxes. The first one is rule-based and the second one is a combination of damage curve approach and rule-based approach. The third one is using Quadratic Discriminant Analysis and the final one is a combination of the first three. Gearbox data from the 2008 Prognostic and Health Management (PHM) conference challenge were used to evaluate our algorithms. The results are close to those top performers in the PHM Challenge.

引用

页数：8

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