Abstract: In this paper, an optimal solution method is proposed for determining the location of
change, i.e. damage, within a perturbed system utilizing a nonlinear pseudo-second order search
algorithm based on function evaluations and gradient information. This method is applied to
damped vibrating systems and utilizes stiffness matrix sensitivities to determine the direction of
search within the estimation. The site of damage (location of change) is the solution which
minimizes the error between the predicted and measured change. A by-product of the Levenberg-
Marquardt algorithm is an estimation of the magnitude of the change within the system which
correlates to damage extent. A second-order model of a dynamic system is used, and an
approximation is developed to describe small perturbations within the system.
Abstract: Dynamic and static identification of a full scale moment-resisting steel-concrete
composite structure with partial strength joints that was tested by means of the pseudo-dynamic
testing technique at the ELSA laboratory of the Joint Research Centre at Ispra, Italy, is the subject
of this paper. The structure was subjected to pseudo-dynamic and dynamic tests at different damage
and peak ground acceleration levels; and the results were used for identifying the behaviour of the
structure. Two and three-dimensional refined finite element models of the structure accompanied by
a robust nonlinear optimization method, the Powell’s Dog Leg method, were updated in order to
reproduce in an optimal fashion the experimental static and dynamic behaviour of the structure.
Abstract: The Dynamic Damage Locating Vector (DDLV) technique localizes damage by
interrogating changes in transfer matrices G. It is shown that although G cannot be computed in a
stochastic setting a surrogate matrix whose null space is related to that of G can be extracted and
this matrix suffices. The paper reviews the theoretical support for the DDLV approach, discusses
the constraints used to obtain the surrogate for G, and illustrates the technique using a 12-DOF
shear beam monitored with 6 sensors.
Abstract: This paper presents experimental study on dispersive waves propagation in steel rails.
The propagation of longitudinal and transverse waves was generated by an impulse hammer and
measured in three points. Wavelet transform (WT) and short time Fourier transform (STFT) were
applied to analyze the time signals. Analysis of signal by STFT does not provide a proper timefrequency
representation due to a fixed size window. The wavelet transform can effectively identify
the time-frequency components in waves. The wavelet signal processing of the experimental wave
propagation signals is intended to be used for rail flaw detection.
Abstract: The paper presents an experimental application of the Proper Orthogonal Decomposition
(POD) to damage detection in steel beams. A damaged beam has been excited with a sinusoidal
force, the acceleration response at points regularly spaced along the structure has been recorded and
the relevant Proper Orthogonal Modes calculated. In this way it is possible to locate damage by
comparing the measured dominant Proper Orthogonal Mode with a smoothed version of it which
does not exhibit apparent peaks in correspondence with the damage.
One of the principal advantages of the proposed damage detection technique is that it does not
require vibration measurements to be performed on the undamaged structure. Moreover the
‘optimality’ of the proper orthogonal modes only requires the use of a few (one-two) of them which
can be computed in real time during lab experiments or while the structure is functioning in the
Abstract: This work aims at the precise assessment of a recently introduced method that, in addition
to damage detection, allows for complete and accurate damage identification (localization)
and magnitude estimation. The method is based on Vector–dependent Functionally Pooled (VFP)
models and is capable of offering an effective and precise solution in a unified framework. The effectiveness
of the method is experimentally assessed via its application to a prototype GARTEURtype
laboratory scale aircraft structure.
Abstract: The reduced-order model of a time-invariant linear dynamical system, excited by a force
of an impulsive type, may be readily obtained using the Ho-Kalman minimal-realization algorithm
. The method is based upon a particular factorization of the Hankel matrix in the Markovian
representation of the discrete-time process. For stochastic systems, the applicability of the theory
has been demonstrated by Akaike  on the assumption that the excitation is a zero-mean white
noise of a gaussian type. Some of the most widely known output-only identification methods, such
as Eigensystem Realization Algorithm (ERA), Canonical Variate Analysis (CVA), and Balanced
Realization (BR)) are based upon the above-mentioned work, with the aid of a robust factorization
technique, such as Singular-Value Decomposition (SVD). Notwithstanding the growing popularity
of the above methods, some aspects of their applicability are not yet understood. Two points are of
particular interest: the first regards the applicability of the theory in highly damped systems; and the
second regards its applicability to systems driven by excitations different from the one
hypothesized. The aim of the present work is to define a reliable test on the hypotheses. Some
numerical and experimental results are presented.
Abstract: Acoustic emission monitoring was completed on a painted aerospace grade steel landing
gear component undergoing fatigue loading until rupture. A post-test linear location analysis of the
collected signals revealed eleven groups where high activity (greater than 2000 hits) occurred
within a defined location, three of which corresponded in location to the position of fracture and
final rupture of the specimen. Feature data, such as amplitude, rise-time, energy etc. were used to
describe the identified signals in each group. A dimension reduction through principal component
analysis of the feature data of all groups was performed. Results showed that high amplitude signals
associated with four groups of signals arising from noise could be separated from the fracture
groups. However four groups not associated with noise or the known positions of the fracture
groups were not separable from the signals attributed to fractures. The paint layer of the specimen
was removed and a magnetic particle investigation was completed that showed these four groups
coincided with regions of additional fracture in the component.
Abstract: This work was conducted as part of the European Union project ARTIMA and it
investigates the effectiveness of wavelets in damage detection. It examines whether a prior wavelet
decomposition of Lamb wave responses facilitates the classification of structural damage. The
structure in question is an aluminium plate with viscoelastic-mounted transducers, and the damage
took the form of saw cuts on the plate. The novelty detection technique of outlier analysis was used
to classify the damage.
Abstract: The electro-mechanical (E/M) impedance-based method is one important and effective
method in damage detection. The basic concept of the impedance method is to monitor the
variations in the structural mechanical impedance spectrum caused by damage in the structure.
Comparing the impedance spectrum to a baseline measurement of the undamaged structure, the real
part of the E/M impedance reflects the state of structural health in the local area, therefore, the
structural damage can be localized, a local-area self-sensing method is implemented.
In this paper, an aluminium plate mounted on an electromagnetic shaker is used to detect
growing fatigue damage using the impedance method. The growing damage is documented by an
increase of the indicators. For the case of a static artificial damage the concept is also demonstrated
to an Airbus A320 fuselage part using 9 self-sensing elements on the stringers.