American Society of Civil Engineers


Damage Detection and Localization in Structures: A Statistics Based Algorithm Using a Densely Clustered Sensor Network


by Elizabeth L. Labuz, (Graduate student, Department of Civil and Environmental Engineering, Lehigh University, 117 ATLSS Drive, Bethlehem, PA 18015. E-mail: elabuz@lehigh.edu), Shamim N. Pakzad, (P.C. Rossin Assistant Professor, Department of Civil and Environmental Engineering, Lehigh University, 117 ATLSS Drive, Bethlehem, PA 18015. E-mail: pakzad@lehigh.edu), and Liang Cheng, (Associate Professor, Department of Computer Science and Engineering, Lehigh University, 326 Packard Lab, Bethlehem, PA 18015. E-mail: cheng@cse.lehigh.edu)
Section: Bridges, pp. 53-64, (doi:  http://dx.doi.org/10.1061/41171(401)6)

     Access full text
     Purchase Subscription
     Permissions for Reuse  

Document type: Conference Proceeding Paper
Part of: Structures Congress 2011
Abstract: Damage prognosis for structural health monitoring is a challenging and complex research topic in civil engineering. Early and accurate damage detection is essential to maximizing the useful life of structures. The use of densely clustered sensor networks provides promising applications in the analysis of structural components and identification of local damage. The proposed localized damage detection method utilizes a linear regression analysis to monitor changes in the linear behavior of a structure with the onset of damage. The structural responses at various sensor locations along a structure are compared to those of other locations and pair-wise influence coefficients are estimated. These coefficients serve as damage indicators when damaged values are compared to healthy-state values. By statistically comparing the change in influence coefficients, structural damage can be accurately and effectively identified. The method is verified using simulations and an experimental prototype of a local beam-column connection, as well as a simulated model of a two-span bridge girder.


ASCE Subject Headings:
Damage
Localization
Statistics
Algorithms
Probe instruments
Monitoring