Application of Spectral Kurtosis to Acoustic Emission Signatures from Bearings

被引：0

作者：

Eftekharnejad, Babak ^{[1
]}

Hamel, Mhmod ^{[2
]}

Addali, Abdulmajid ^{[2
]}

Mba, David ^{[2
]}

机构：

[1] Renewable Energy Syst Ltd, Kings Langley WD4 8LR, Herts, England

[2] Cranfield Univ, Sch Engn, Cranfield MK43 0AL, Beds, England

来源：

CONDITION MONITORING OF MACHINERY IN NON-STATIONARY OPERATIONS | 2012年

关键词：

DIAGNOSTICS; VIBRATION; SIGNALS; FAULTS;

D O I：

暂无

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

The application of Acoustic Emission (AE) in condition monitoring of rotating machines has been well documented. The majority of research works in this field has involved the use of conventional time domain analysis for processing the AE signals from the machines and there has been little attention given to application of more advanced signal processing methods. This research presents a study in which some advanced signal processing techniques such as Wavelet and Spectral Kurtosis (SK) has been applied to offer improved diagnosis for bearing defect detection

引用

页码：425 / 437

页数：13

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