Premium
Damage detection framework for truss railway bridges utilizing statistical analysis of operational strain response
Author(s) -
Azim Md Riasat,
Gül Mustafa
Publication year - 2020
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.2573
Subject(s) - structural engineering , truss bridge , truss , bridge (graph theory) , parametric statistics , finite element method , engineering , matrix (chemical analysis) , computer science , mathematics , statistics , materials science , medicine , composite material
Summary In this paper, a non‐parametric damage detection method for truss railroad bridges is presented which utilizes statistical analysis of bridge strain responses to operational train loading. Strain time‐history responses obtained under baseline and damaged bridge conditions are used to compute the coefficient of variation matrices. The results are presented in terms of the difference of the covariance matrix of the truss bridge between the baseline and damaged condition. The damage in the bridge is detected and located by observing the coefficients of the difference matrix as structural changes occur in the bridge. The magnitudes of the coefficients could be used to relatively estimate the severity of the damage. A finite element model of a truss railroad bridge is utilized for numerical validation of the proposed method. It is demonstrated that the proposed method yields encouraging results for identifying, locating, and relatively assessing the damage even under different operational conditions (e.g., different train speeds and loads). The proposed method could be very useful for early detection of damage and thus could assist in developing effective maintenance strategies for railway bridges.