Key Engineering Materials Vol. 347

Abstract: The object of this paper is to illustrate the use of novelty detection techniques in Structural Health Monitoring (SHM) by the consideration of a number of case studies of varying complexity, from a simple lumped-mass system to an FE model of an offshore structure to an experimental study of an aircraft wing.

Abstract: Computational model updating techniques are used to adjust selected parameters of finite element models in order to make the models compatible with experimental data. This is done by minimizing the differences of analytical and experimental data, for example, natural frequencies and mode shapes by numerical optimization procedures. For a long time updating techniques have also been investigated with regard to their ability to localize and quantify structural damage. The success of such an approach is mainly governed by the quality of the damage model and its ability to describe the structural property changes due to damage in a physical meaningful way. Our experience has shown that due to unavoidable modelling simplifications and measurement errors the changes of the corresponding damage parameters do not always indicate structural modifications introduced by damage alone but indicate also the existence of other modelling uncertainties which may be distributed all over the structure. This means that there are two types of parameters which have to be distinguished: the damage parameters and the other parameters accounting for general modelling and test data uncertainties. Although these general parameters may be physically meaningless they are necessary to achieve a good fit of the test data and it might happen that they cannot be distinguished from the damage parameters. For complex industrial structures it is seldom possible to generate unique structural models covering all possible damage scenarios so that one has to expect, that the parameters introduced for describing the damage will not be fully consistent with the physical reality. This is the reason why in the scientific community there is still some doubt if model based techniques can be used at all for practical purposes of damage detection and quantification under in-situ environment conditions. In the present paper we summarize the methodology of computational model updating and report about our experience with damage identification exemplified by practical examples. A new technique and an application of localising and quantifying the damage from updating the parameters of the damaged and the undamaged models simultaneously using the differences of the test data from the damaged and the undamaged structure is also presented. In this application we used the deflections (influence lines) of a beam structure measured under a slowly moving load.

Abstract: Architectural heritage is a resource and a fundamental part of the cultural European background; it also causes concern, due to the huge investment needed to maintain it, or even to repair it after environmental injuries. The Author is general coordinator of an Italian National research project aimed to formulate new guidelines for structural health monitoring and survey of historical and monumental structures. The Project programme traces a general strategy to build maintenance related monitoring procedures, to face the problems of data uncertainties, to propose robust approaches. This paper shows the general path traced for that project, just now at its start-up phase, but the main attention is addressed to the robust approaches to dynamic testing and model updating.

Abstract: Two finite-element-based, full-field computational methods and algorithms for use in Structural Health Management (SHM) systems are reviewed. Their versatility, robustness, and computational efficiency make them well suited for real-time, large-scale space vehicle, structures, and habitat applications. The methods may be effectively employed to enable real-time processing of sensing information, specifically for identifying three-dimensional deformed structural shapes as well as the internal loads. In addition, they may be used in conjunction with evolutionary algorithms to design optimally distributed sensors. These computational tools have demonstrated substantial promise for utilization in future SHM systems.

Abstract: This paper presents the perspective of the Structural Mechanics program of the Air Force Office of Scientific Research on the damage assessment of structures. It is found that damage assessment of structures plays a very important role in assuring the safety and operational readiness of Air Force fleet. The current fleet has many aging aircraft, which poses a considerable challenge for the operators and maintainers. The nondestructive evaluation technology is rather mature and able to detect damage with considerable reliability during the periodic maintenance inspections. The emerging structural health monitoring methodology has great potential, because it will use on-board damage detection sensors and systems, will be able to offer on-demand structural health bulletins. Considerable fundamental and applied research is still needed to enable the development, implementation, and dissemination of structural health monitoring technology.

Abstract: A method for damage localisation has been developed, which is based on the phased array idea. Four arrays of transducers, instead of only one, are used to perform a beam-forming procedure. Each array consists of nine transducers placed along a line, which are able to excite and register elastic waves. The arrays are placed in such a way that the angular difference between them is 45º and the rotation point is the middle transducer, which is common for all the arrays. The idea has been tested on a square aluminium plate modelled by the Spectral Finite Element Method. Two types of damage were considered, namely distributed damage, which was modelled as stiffness reduction, and cracks, modelled as separation of nodes in selected finite elements. The plate is excited by a wave packet (5-cycle sine modulated by the Hanning window). The whole array system is placed in the middle of the plate. Each phase array in the system acts independently and produces maps of a scanned field based on the beam-forming procedure. These maps are made of signals that represent the difference between the damaged plate signals and those from the intact plate. An algorithm was developed to join all four maps. This procedure eliminates the necessity to analyse each map individually and also gives the possibility to extract common features only. It allows to remove ambiguity and helps to localise damage more precisely than in the case of a single map. The problem for damage localisation was investigated and exemplary maps confirming the effectiveness of the system proposed were obtained. The investigation is based exclusively on numerical data.

Abstract: In recent years, several structures have been equipped with permanent monitoring systems, able to record the response both in terms of displacements and strains over very long periods of time and, theoretically, for the entire life of the structure. Despite of the number of applications, very few studies have been presented focused on the interpretation of the data without the study of a numerical model of the structure. Since an optimal and unique algorithm cannot be proposed depending on the variety of applications, the aim of the work is to propose a multi-algorithm methodology as a tool for detecting and localizing the insurgence of damage or material degradation from the measurements taken during a continuous static monitoring of civil structures. A method based on Principal Component Analysis will be proposed in order to compare the responses and detect the insurgence of anomalous behaviors. The algorithm will be first tested on simulated data deriving from a numerical benchmark with sensors and different damage scenarios, then the proposed methodology will be validated on a real structure. In this second application, due to the great number of installed sensors, the algorithm will be integrated with a preliminary analysis in order to cluster and gather together the sensors with a comparable behavior and a similar sensitivity to damage.