Claus-Peter Fritzen

Multi-site damage localization in anisotropic plate-like structures using an active guided wave structural health monitoring system

A new approach for structural health monitoring using guided waves in plate-like structures has been developed. In contrast to previous approaches, which mainly focused on isotropic or quasi-isotropic plates, the proposed algorithm does not assume any simplifications regarding anisotropic wave propagation. Thus, it can be used to improve the probability of detection. In this paper the mathematical background for damage localization in anisotropic plates will be introduced. This is an extension of the widely known ellipse method. The formalism is based on a distributed sensor network, where each piezoelectric sensor acts in turn as an actuator. The automatic extraction of the onset time of the first waveform in the differential signal in combination with a statistical post-processing via a two-dimensional probability density function and the application of the expectation-maximization algorithm allows a completely automatic localization procedure. Thus, multiple damages can be identified at the same time. The present study uses ultrasonic signals provided by the spectral element method. This simulation approach shows good agreement with experimental measurements. A local linear neural network is used to model the nonlinear dispersion curves. The benefit of using a neural network approach is to increase the angular resolution that results from the sparse sensor network. Furthermore, it can be used to shorten the computational time for the damage localization procedure.

Vibration-Based Structural Health Monitoring – Concepts and Applications

This paper gives an overview on the current status of vibration-based methods for Structural Health Monitoring. All these methods have in common that a structural change due to a damage results in a more or less pronounced change of the dynamic behavior. The use of modal information is discussed, as well as the direct use of forced and ambient vibrations. From this information, different strategies can be deduced which depend on the type of measurement data (time/frequency domain) but also on the frequency spectrum. The incorporation of actuation and sensing devices into the structure leads to modern concepts of Smart Structural Health Monitoring. Examples from civil and aerospace engineering show the applicability of these methods.

An Updated Comparison of the Force Reconstruction Methods

For purposes of monitoring and damage prognosis it is important to know the external loads which act on a structure. The knowledge of these loads enables us to make an assessment of damage after extreme events and updated forecasts of the remaining life-time. In many practical applications it is not possible to measure the forces e.g. resulting from wind loads or traffic directly. Therefore, these forces are determined indirectly from dynamic measurements. In this contribution, an updated overview of available time domain load reconstruction methods is presented. An attempt of highlighting the main advantages and disadvantages of different approaches, which are used in engineering is done. The importance of sensors type as well as their locations is considered for each approach. Finally, the methods applicability to real structures, where the online reconstruction plays an important role, is discussed.

A finite element updating approach for identification of the anisotropic hyperelastic properties of normal and diseased aortic walls from 4D ultrasound strain imaging.

Computational analysis of the biomechanics of the vascular system aims at a better understanding of its physiology and pathophysiology and eventually at diagnostic clinical use. Because of great inter-individual variations, such computational models have to be patient-specific with regard to geometry, material properties and applied loads and boundary conditions. Full-field measurements of heterogeneous displacement or strain fields can be used to improve the reliability of parameter identification based on a reduced number of observed load cases as is usually given in an in vivo setting. Time resolved 3D ultrasound combined with speckle tracking (4D US) is an imaging technique that provides full field information of heterogeneous aortic wall strain distributions in vivo. In a numerical verification experiment, we have shown the feasibility of identifying nonlinear and orthotropic constitutive behaviour based on the observation of just two load cases, even though the load free geometry is unknown, if heterogeneous strain fields are available. Only clinically available 4D US measurements of wall motion and diastolic and systolic blood pressure are required as input for the inverse FE updating approach. Application of the developed inverse approach to 4D US data sets of three aortic wall segments from volunteers of different age and pathology resulted in the reproducible identification of three distinct and (patho-) physiologically reasonable constitutive behaviours. The use of patient-individual material properties in biomechanical modelling of AAAs is a step towards more personalized rupture risk assessment.

Online Simultaneous Reconstruction of Wind Load and Structural Responses—Theory and Application to Canton Tower

The actual wind load information is helpful in evaluating the health status of high-rise structures. However, as a type of distributed load, the wind load is very difficult to be measured directly. A possible solution is to reconstruct it from the structural response measurements. This is often an ill-posed inverse problem. In this article, such ill posedness is solved by using a stable input estimator. With the help of the proposed application-oriented algorithm selection guidance, a type of state and input estimator is formulated. This type of estimator is designed based on the Kalman filter scheme, and is capable of estimating the unknown inputs and the system states within one sampling time. This actually facilitates the online simultaneous reconstruction of the wind load and the structural responses. The 600 m tall Canton Tower is situated in a typhoon active area, and a structural health monitoring system has already been integrated onto this tower. These two points make the Canton Tower an ideal test bed for validating the above illustrated online reconstruction strategy for the wind load and the structural responses. An operational modal analysis (OMA) is first performed to identify the modal properties of the Canton Tower under the Typhoon Nanmadol in 2011. Then a reduced-order finite element model (FEM) of the Canton Tower is updated according the OMA results. Finally, the equivalent fluctuating lateral loads and moments, which act on the nodes of the reduced-order FEM are reconstructed using the acceleration measurements recorded during Tyhoon Kai-tak in 2012. The reconstruction results are validated by comparing the simultaneously reconstructed structural acceleration with the corresponding sensor measurements. The mean component of the loads and moments are calculated using the real-time wind speed measurements and the available aerodynamic force coefficients. It is noted here that the focus of this article is not to develop a totally new theory, but rather to explore the application of a state and input estimator in the foreground to a practical complex structure.

Wave energy trapping and localization in a plate with a delamination

The research aims at an experimental approval of the trapping mode effect theoretically predicted for an elastic plate-like structure with a horizontal crack. The effect is featured by a sharp capture of incident wave energy at certain resonance frequencies with its localization between the crack and plate surfaces in the form of energy vortices yielding long-enduring standing waves. The trapping modes are eigensolutions of the related diffraction problem associated with nearly real complex points of its discrete frequency spectrum. To detect such resonance motion, a laser vibrometer based system has been employed for the acquisition and appropriate visualization of piezoelectrically actuated out-of-plane surface motion of a two-layer aluminum plate with an artificial strip-like delamination. The measurements at resonance and off-resonance frequencies have revealed a time-harmonic oscillation of good quality above the delamination in the resonance case. It lasts for a long time after the scattered waves have left that area. The measured frequency of the trapped standing-wave oscillation is in a good agreement with that predicted using the integral equation based mathematical model.

Data-driven multivariate algorithms for damage detection and identification: Evaluation and comparison

This article is concerned with the experimental validation of a structural health monitoring methodology for damage detection and identification. Three different data-driven multivariate algorithms are considered here to obtain the baseline pattern. These are based on principal component analysis, independent component analysis and hierarchical non-linear principal component analysis. The contribution of this article is to examine and compare the three proposed algorithms that have been reported as reliable methods for damage detection and identification. The approach is based on a distributed piezoelectric active sensor network for the excitation and detection of structural dynamic responses. A woven multilayered composite plate and a simplified aircraft composite skin panel are used as examples to test the approaches. Data-driven baseline patterns are built when the structure is known to be healthy from wavelet coefficients of the structural dynamic responses. Damage is then simulated by adding masses at different positions of the structures. The data from the structure in different states (damaged or not) are then projected into the different models by each actuator in order to generate the input feature vectors of a self-organizing map from the computed components together with squared prediction error measures. All three methods are shown to be successful in detecting and classifying the simulated damages. At the end, a critical comparison is given in order to investigate the advantages and disadvantages of each method for the damage detection and identification tasks.

Data-driven methodology to detect and classify structural changes under temperature variations

This paper presents a methodology for the detection and classification of structural changes under different temperature scenarios using a statistical data-driven modelling approach by means of a distributed piezoelectric active sensor network at different actuation phases. An initial baseline pattern for each actuation phase for the healthy structure is built by applying multiway principal component analysis (MPCA) to wavelet approximation coefficients calculated using the discrete wavelet transform (DWT) from ultrasonic signals which are collected during several experiments. In addition, experiments are performed with the structure in different states (simulated damages), pre-processed and projected into the different baseline patterns for each actuator. Some of these projections and squared prediction errors (SPE) are used as input feature vectors to a self-organizing map (SOM), which is trained and validated in order to build a final pattern with the aim of providing an insight into the classified states. The methodology is tested using ultrasonic signals collected from an aluminium plate and a stiffened composite panel. Results show that all the simulated states are successfully classified no matter what the kind of damage or the temperature is in both structures.

Mechanisms of short-fatigue-crack initiation and propagation in a β-Ti alloy

Abstract The microstructurally short-crack initiation and early propagation were studied on the metastable β-Ti alloy TimetalĽB in the solution heat-treated bcc β microstructure under symmetrical pull-push fatigue testing. By means of a finite-element treatment in combination with local displacement measurements applying a laser interferometric strain-displacement gauge (ISDG), it was shown that elastic anisotropy gives rise to high mechanical stresses at certain grain boundaries (GBs). Large-angle GBs were observed to be preferred sites for short-crack initiation. Two modes of fatigue crack initiation were found: one is crack formation along slip bands, often resulting in transgranular crack propagation; the second is intergranular cracking of GBs. Using electron back-scattered diffraction (EBSD), local crystallographic orientations were determined and hence the role of GB types in the process of short crack initiation and growth could be taken into account. On the basis of the experimental observations and measurements, the preferred crystallographic conditions for short crack initiation and growth were revealed. The ISDG system was applied to measure the local crack opening displacements of short cracks in order to characterize the dependence of the short-crack closure phenomena on the applied load.

Application of model-based damage identification to a seismically loaded structure

The aim of the presented model-based damage identification approach is to detect, localize and quantify changes in a mechanical structure due to damage by means of a computational model and measured changes of the structures dynamic behavior. An inverse sensitivity problem is formulated, leading to a large number of damage parameters when the structure has many structural members. While the number of potential candidates for the damage locations is very large, usually there are only very few active parameters concentrating on the damaged areas. It turns out that the parameter subset selection is an essential step. The method is applied to a large scale structure, the so-called Steelquake structure, a two-storey building, which was subjected to a seismic loading. Cracks at different locations developed during this loading. All crack locations are successfully identified by the algorithm, but one undamaged position was also localized. Additional simulation studies show that errors in the measurement data can cause a false indication of damage.