Abstract

During the Service Life of Structures, Breathing-Fatigue Cracks May Occur in Structural Members Due to Dynamic Loadings Acting on Them. These Fatigue Cracks, If Undetected, Might Lead to a Catastrophic Failure of the Whole Structural System. Although a Number of Approaches Have Been Proposed to Detect Breathing-Fatigue Cracks, Some of Them Appear Rather Sophisticated or Expensive (Requiring Complicated Equipment), and Others Suffer from a Lack of Sensitivity. in This Study, a Simple and Efficient Approach to Detecting Breathing-Fatigue Cracks is Developed based on Dynamic Characteristics of Breathing Cracks. First, Considering that Breathing Cracks Introduce Bilinearity into Structures, a Simple System Identification Method for Bilinear Systems is Proposed by Taking Best Advantage of Dynamic Characteristics of Bilinear Systems. This Method Transfers Nonlinear System Identification into Linear System Identification by Dividing Impulse or Free-Vibration Responses into Different Parts Corresponding to Each Stiffness Region According to the Stiffness Interface. in This Way, the Natural Frequency of Each Region Can Be Identified using Any Modal Identification Approach Applicable to Linear Systems. Second, the Procedure for Identifying the Existence of Breathing Fatigue Cracks and Quantifying the Cracks Qualitatively is Proposed by Looking for the Difference in the Identified Natural Frequency between Regions. Third, through Introducing Hilbert Transform, the Proposed Procedure is Extended to Identify Fatigue Cracks in Piecewise-Nonlinear Systems. the Proposed System Identification Method and Crack Detection Procedure Have Been Successfully Validated by Numerical Simulations and Experimental Tests. © 2012 Elsevier Ltd.

Department(s)

Civil, Architectural and Environmental Engineering

Comments

National Natural Science Foundation of China, Grant 50708029

International Standard Serial Number (ISSN)

1095-8568; 0022-460X

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2023 Elsevier, All rights reserved.

Publication Date

21 Jan 2013

 
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