Review of Techniques for Fault Diagnosis in Damaged Structure and Engineering System

Focus has been made to give an overview of various methodologies used in fault diagnosis and condition monitoring. A crack in vibrating structures can lead to premature failure if it is not detected in time. Researchers have been working on the dynamics of cracked structures for decades to be able t...

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Main Authors: Dhirendra Nath Thatoi, Harish Ch. Das, Dayal R. Parhi
Format: Article
Language:English
Published: SAGE Publishing 2012-01-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1155/2012/327569
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author Dhirendra Nath Thatoi
Harish Ch. Das
Dayal R. Parhi
author_facet Dhirendra Nath Thatoi
Harish Ch. Das
Dayal R. Parhi
author_sort Dhirendra Nath Thatoi
collection DOAJ
description Focus has been made to give an overview of various methodologies used in fault diagnosis and condition monitoring. A crack in vibrating structures can lead to premature failure if it is not detected in time. Researchers have been working on the dynamics of cracked structures for decades to be able to monitor a structure and diagnose fault at the earliest possible stage. An effort has been made in the current paper to understand different techniques and methodologies for fault diagnosis and condition monitoring of damaged structures subjected to varied dynamic loading. The methods used are classical, wavelet transform, and finite element methods, artificial intelligence methods, and numerical and experimental methods. Using classical methods, engineers are able to predict faults. But using artificial intelligence techniques, it is observed that the forecasting time for fault diagnosis improves a lot in comparison to other methodologies.
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spelling doaj.art-ce501380513a4528a9d1342d6398e0cb2022-12-22T01:55:11ZengSAGE PublishingAdvances in Mechanical Engineering1687-81322012-01-01410.1155/2012/32756910.1155_2012/327569Review of Techniques for Fault Diagnosis in Damaged Structure and Engineering SystemDhirendra Nath Thatoi0Harish Ch. Das1Dayal R. Parhi2 Department of Mechanical Engineering, Siksha “O” Anusandhan University, Bhubaneswar 751030, India Department of Mechanical Engineering, Siksha “O” Anusandhan University, Bhubaneswar 751030, India Department of Mechanical Engineering, N.I.T. Rourkela, Rourkela 769008, IndiaFocus has been made to give an overview of various methodologies used in fault diagnosis and condition monitoring. A crack in vibrating structures can lead to premature failure if it is not detected in time. Researchers have been working on the dynamics of cracked structures for decades to be able to monitor a structure and diagnose fault at the earliest possible stage. An effort has been made in the current paper to understand different techniques and methodologies for fault diagnosis and condition monitoring of damaged structures subjected to varied dynamic loading. The methods used are classical, wavelet transform, and finite element methods, artificial intelligence methods, and numerical and experimental methods. Using classical methods, engineers are able to predict faults. But using artificial intelligence techniques, it is observed that the forecasting time for fault diagnosis improves a lot in comparison to other methodologies.https://doi.org/10.1155/2012/327569
spellingShingle Dhirendra Nath Thatoi
Harish Ch. Das
Dayal R. Parhi
Review of Techniques for Fault Diagnosis in Damaged Structure and Engineering System
Advances in Mechanical Engineering
title Review of Techniques for Fault Diagnosis in Damaged Structure and Engineering System
title_full Review of Techniques for Fault Diagnosis in Damaged Structure and Engineering System
title_fullStr Review of Techniques for Fault Diagnosis in Damaged Structure and Engineering System
title_full_unstemmed Review of Techniques for Fault Diagnosis in Damaged Structure and Engineering System
title_short Review of Techniques for Fault Diagnosis in Damaged Structure and Engineering System
title_sort review of techniques for fault diagnosis in damaged structure and engineering system
url https://doi.org/10.1155/2012/327569
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