INSTITUTE OF PHYSICS PUBLISHING SMART MATERIALS AND STRUCTURES
Smart Mater. Struct. 12 (2003) 776–784 PII: S0964-1726(03)67504-X
Structural health monitoring and
damage detection using a sub-domain
inverse method
F J Carrion
1
, J F Doyle
2
and A Lozano
3
1
Instituto Mexicano del Transporte, Km 12000 Carretera Quer´ etaro-Galindo,
Sanfandila Municipio de Pedro Escobedo, 76700 Quer´ etaro, Mexico
2
Aeronautics and Aerospace Department, Purdue University, West Lafayette, IN, USA
3
Consejo de Ciencia y Tecnolog´ ıa del Estado de Quer´ etaro, 76000 Quer´ etaro, Mexico
Received 26 April 2002, in final form 19 June 2003
Published 25 September 2003
Online at stacks.iop.org/SMS/12/776
Abstract
Health monitoring of modern complex structures poses new challenges as
regards increased safety and operational reliability, while recent sensor
technology opens up many possibilities for previously undreamt of methods
of analysis. The need for different schemes or algorithms for damage
detection, remote monitoring and continuous real time evaluation is
increasingly pressing.
In this work, a sub-domain inverse method based on the analysis of the
wave propagation in structures is used for the identification of the damage
response vectors, with an adapted minimum rank perturbation formulation
for the calculation of the perturbation stiffness matrix of a damaged
structure.
Results show that simple experimental procedures can be utilized and
several strategies can be adopted for fast monitoring or detailed analysis.
Analyses in sub-regions or complete structures are possible and testing can
be done under random excitations and with structural non-linear behaviour
or unknown structural parameters. The proposed method of using smart
structures with many embedded sensors is potentially useful for structural
health monitoring and damage detection with almost no limitation on the
type or distribution of the sensors.
(Some figures in this article are in colour only in the electronic version)
1. Introduction
Modern civil and aeronautical structures are getting more
complex in size and design, new concepts and materials are
increasingly being used and the environmental and operational
conditions are ever more demanding. Moreover, structures
are becoming important components of integrated systems
(e.g. highway bridges in integrated transport systems); for
these, continuous evaluation of the structural condition is
necessary and, in some cases, it must be in real time [1].
At the same time, sensor technology has grown and has
expanded very many possibilities for measuring, evaluation
and control of engineering systems; multiple sensors of
different types are now affordable and we can envisage the use
of thousands of embedded sensors in smart structures [2–4].
Under these operational conditions, health monitoring of
new structures and sensor technology developments pose
various challenges and alternatives for innovative theory and
experimental schemes [5].
Structural evaluation to determine damage, deterioration
and/or operational anomalies in modern complex civil
and aeronautic structures is essential to determine safety,
operational reliability and residual life [1]. Traditionally,
most of the damage detection programs are based on visual
inspections, which are costly and difficult to carry out due
to the inaccessibility of most of the parts of the structure.
Furthermore, internal damage cannot be detected and no
quantitative value of the damage and the residual strength
of the structure is produced by the visual inspections [6].
Recent health monitoring systems have included different non-
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