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193822

Rotary Machines Fault Diagnosis based on Principal Component Analysis

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Last updated: 24 Dec 2024

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Abstract

  Rotating machines are commonly used in industrial applications. Mechanical faults such as rotor unbalance, shaft misalignment, pulley misalignment, structural looseness, and bearing faults leading to unplanned shutdown based on the severity of these faults. The condition monitoring technique based on vibration analysis has the potential to detect and diagnose a great number of early stage faults. However, some mechanical faults have correlated vibration features leading to ambiguous diagnosis to identify and distinguish these faults. In this paper, a proposed method based on the Principal Component Analysis (PCA) is presented to produce uncorrelated Principal Components (PCs) to identify the healthy and different faulty cases. A test rig was prepared to simulate a group of mechanical faults such as rotor unbalance, pulley misalignment, belt damage, combined unbalance with pulley misalignment, and combined unbalance with belt damage. The conventional vibration measurements were collected for each case and their features were extracted and used to produce the equivalent PCs. It was found that the produced uncorrelated PCs have the superior to distinguish the majority of simulated faults which have correlated vibration features as presented in the rest of paper.    

DOI

10.21608/erj.2021.193822

Keywords

condition monitoring, Vibration

Authors

First Name

M.

Last Name

Elsamanty

MiddleName

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Affiliation

Faculty of Engineering at Shoubra, Benha University, 108 Shoubra St., Cairo, Egypt Smart Engineering Systems Research Center (SESC), Nile University, 12588, Shaikh Zayed City, Giza, Egypt

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Orcid

-

First Name

W.

Last Name

S. Salman

MiddleName

-

Affiliation

Faculty of Engineering at Shoubra, Benha University, 108 Shoubra St., Cairo, Egypt Fayoum University, Faculty of Engineering, Mechanical Department, Fayoum, Egypt

Email

-

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-

Orcid

-

First Name

A.

Last Name

A. Ibrahim

MiddleName

-

Affiliation

Faculty of Engineering at Shoubra, Benha University, 108 Shoubra St., Cairo, Egypt

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-

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-

Orcid

-

Volume

171

Article Issue

0

Related Issue

27526

Issue Date

2021-09-01

Receive Date

2021-09-09

Publish Date

2021-09-01

Page Start

138

Page End

150

Print ISSN

1110-5615

Article File

ERJ_Volume 171_Issue 0_Pages 138-150.pdf

PDF . 850.8kB

Link

https://erj.journals.ekb.eg/article_193822.html

Detail API

https://erj.journals.ekb.eg/service?article_code=193822

Order

9

Type

Original Article

Type Code

998

Publication Type

Journal

Publication Title

Engineering Research Journal

Publication Link

https://erj.journals.ekb.eg/

MainTitle

Rotary Machines Fault Diagnosis based on Principal Component Analysis

Details

Type

Article

Created At

22 Jan 2023