Ball Bearing Damage Detection Using Traditional Signal Processing Algorithms

被引：63

作者：

Bediaga, Inigo

Mendizabal, Xabier

Arnaiz, Aitor

Munoa, Jokin

机构：

[1] Dynamics and Control Engineering Department

[2] RandD Department, SORALUCE S. Coop.

[3] Diagnostics and Prediction Unit, TEKNIKER

[4] University of Navarra

来源：

IEEE INSTRUMENTATION & MEASUREMENT MAGAZINE | 2013年 / 16卷 / 02期

关键词：

Damage detection - Fault detection - Machine tools - Signal detection;

D O I：

10.1109/MIM.2013.6495676

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Fault detection and diagnosis of ball bearings has always been a challenge when monitoring rotating machinery. Specifically, bearing diagnostics have seen extensive research in the field of fault detection and diagnosis. This article reviews traditional algorithms used to detect and diagnose faulty bearings in heavy-duty milling machine tool spindle heads. Different kinds of faults have been created deliberately on the bearings of a test spindle head. The prediction effectiveness of several detection methods are tested when faults are in different stages of development. © 1998-2012 IEEE.

引用

页码：20 / 25

页数：6

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[3]

Harris T. A., 2000, ROLLING BEARING ANAL

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