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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Sharif University of Technology</PublisherName>
				<JournalTitle>Scientia Iranica</JournalTitle>
				<Issn>1026-3098</Issn>
				<Volume>25</Volume>
				<Issue>Issue 6: Special Issue Dedicated to Professor Goodarz Ahmadi</Issue>
				<PubDate PubStatus="epublish">
					<Year>2018</Year>
					<Month>12</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A modified wavelet energy rate-based damage identification method for steel bridges</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>3210</FirstPage>
			<LastPage>3230</LastPage>
			<ELocationID EIdType="pii">20736</ELocationID>
			
<ELocationID EIdType="doi">10.24200/sci.2018.20736</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Mohammad</FirstName>
					<LastName>Noori</LastName>
<Affiliation>International Institute for Urban Systems Engineering, Southeast University, Nanjing 210096, China, Mechanical Engineering and ASME Fellow, California Polytechnic State University, San Luis Obispo, California, USA</Affiliation>

</Author>
<Author>
					<FirstName>Haifeng</FirstName>
					<LastName>Wang</LastName>
<Affiliation>State University of New York, Buffalo, NY 14260, USA</Affiliation>

</Author>
<Author>
					<FirstName>Wael A.</FirstName>
					<LastName>Altabey</LastName>
<Affiliation>International Institute for Urban Systems Engineering, Southeast University, Nanjing 210096, China, Nanjing Zhixing Information Technology Company Nanjing, China</Affiliation>

</Author>
<Author>
					<FirstName>Ahmad I. H.</FirstName>
					<LastName>Silik</LastName>
<Affiliation>International Institute for Urban Systems Engineering, Southeast University, Nanjing 210096, China.</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2018</Year>
					<Month>03</Month>
					<Day>12</Day>
				</PubDate>
			</History>
		<Abstract>&lt;em&gt;Strain is sensitive to damage, especially in steel structures. But traditional strain gauge does not fit bridge damage identification because it only provides the strain information of the point where it is set up. While traditional strain gauges suffer from its drawbacks, long-gage FBG strain sensor is capable of providin&lt;/em&gt;g &lt;em&gt;the strain information of a certain range, which all the damage information within the sensing range can be reflected by the strain information provided by FBG sensors. The wavelet transform is a new way to analyze the signals, which is capable of providing multiple levels of details and approximations of the signal. In this paper, a wavelet packet transform-based damage identification is proposed for the steel bridge damage identifications numerically and with experimental experiment to validate the proposed method. The strain data obtained via long-gage FBG strain sensors are transformed into a modified wavelet packet energy rate index first to identify the location and severity of damage. The results of numerical simulations show that the proposed damage index is a good candidate which is capable of identifying both the location and severity of damage under noise effect&lt;/em&gt;.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">FBG strain sensor</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Wavelet packet transform</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Damage identification</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Modified wavelet packet energy rate</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://scientiairanica.sharif.edu/article_20736_dba82e84e38d370c562120b20abb1449.pdf</ArchiveCopySource>
</Article>
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