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Eingeladener Vortrag
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Fault detection for linear parameter varying systems under changes in the process noise covariance
(2020)
Detecting changes in the eigenstructure of linear systems is a comprehensively investigated subject. In particular, change detection methods based on hypothesis testing using Gaussian residuals have been developed previously. In such residuals, a reference model is confronted to data from the current system. In this paper, linear output-only systems depending on a varying external physical parameter are considered. These systems are driven by process noise, whose covariance may also vary between measurements. To deal with the varying parameter, an interpolation approach is pursued, where a limited number of reference models -- each estimated from data measured in a reference state -- are interpolated to approximate an adequate reference model for the current parameter. The problem becomes more complex when the different points of interpolation correspond to different noise conditions. Then conflicts may arise between the detection of changes in the eigenstructure due to a fault and the detection of changes due to different noise conditions. For this case, a new change detection approach is developed based on the interpolation of the eigenstructure at the reference points. The resulting approach is capable of change detection when both the external physical parameter and the process noise conditions are varying. This approach is validated on a numerical simulation of a mechanical system.
Planar tomography and numerical analysis for damage characterization of impact loaded RC plates
(2020)
The damage analysis of reinforced concrete (RC) is of high interest for reasons of effective maintenance and structural safe-ty of buildings. The damage structures of RC plates loaded by an impact were investigated, applying X-ray planar tomogra-phy and finite element method (FEM). Planar tomography allows getting three-dimensional information of the RC elements and the damage including crack, spalling and scabbing. The FEM model validated on the tomography data justifies the appli-cation for further predictions of the damage description. In this study, we investigated concrete plates of three different thick-ness subjected to impacts at different low- and medium-velocity, whereby the used impactor had a flat tip, which resulted in small penetrations on the front side and scabbing on the rear side. In order to quantify the damage, the damage volume and its distribution through the plate were computed and the correlations between degree of damage and impact velocity were found out.
Due to the wide range of applications, the easy production and the large field of use, reinforced concrete (RC) is a widespread building material. This variety of applications is reflected in a wide range of physical material properties. Not only therefor it still is a technical challenge to provide all necessary test conditions for experimentally reproducing dynamic effects under impact loading of RC structures. In this paper we present investigations on the thicknesses of RC plates under low and medium high velocity impact loading by a flat-tipped impactor. The planar tomography setup at BAM is used to visualize the impact damage and to characterize the damage features such as cracks, scabbing and spalling. Further, the comparison of tomography results with those of an applied numeric simulation analysis is used to verify the numeric models for future damage prognosis under impact loading. Using the results of both, the tomographic as well as the FE analysis, different damage features were investigated and compared regarding their validity. Crack damage plays a leading part and the significance of summarized crack values as well as their distribution is analyzed. The total damage value but also the determined damage distribution both provide an input for describing damage as a function of the impactor velocity and plate thickness.
Classic non-destructive fatigue crack detection methods reveal the state of the fatigue damage evolution at the moment of application, generally not under operational conditions. The here introduced crack luminescence method realizes a clear visibility of the occurred and growing crack in loaded components during operation. Different established experiments show that due to the sensitive coating a crack Formation can be detected even in early stage under the premise the crack reached the surface. The coating consists of two layers with different properties and functions. The bottom layer emits light as fluorescence under UV radiation. The top layer covers the fluorescing one and prevents the emitting of light in case of no damage at the surface. In case of surface crack occurrence, the luminescent light is clearly noticeable by visual observations and also by standard camera equipment which makes automated crack detection possible as well. It is expected that crack luminescence can increase structural safety as well as reduce costs and time for inspections and preventive maintenance.
Reinforced concrete (RC) is used as structural material in most diverse civil engineering applications. For the variability of its physical properties it is still an engineering challenge to meet all necessary requirements for the prediction of dynamic effects under impact loading. In this paper, investigations are shown within the scope of quantifying and evaluating the damage caused by an impact. The experimental investigations are performed in the field of low- and medium-velocity impact. The chosen flat nose shape results in small penetrations on the top side and scabbing on the bottom side. The plate is scanned with an adapted planar tomographic examination after the impact, and the damage is analysed, afterwards. Cracks and spalling are made visible with a reconstruction. The numerical model validated on the tomographic results justifies the application for further predictions of the damage description.
Environmental based perturbations influence significantly the ability to identify structural dam-age in Structural Health Monitoring. Strategies are needed to classify such effects and consider them appropri-ately in SHM. It has to be considered if seasonal effects just mask the structural response or if temperature itself correlates to a weakening of the structure. Various methods have been developed and analyzed to separate environmental based effects from damage induced changes in the measures. Generally, two main approaches have emerged from research activity in this fields: (a) statistics-based tools analyzing patterns in the data or in computed parameters and (b) methods, utilizing the structural model of the bridge considering environmental as well as damage-based changes of stiffness values. With the background of increasing affordability of sensing and computing technology, effort should be made to increase sensitivity, reliability and robustness of proce-dures, separating environmental from damage caused changes in SHM measures. The contribution describes an attempt to evaluate both general strategies, their advantages and drawbacks. In addition, two vibration moni-toring procedures are introduced, allowing for temperature-based perturbations of the monitoring data.
At present, to produce renewable energy offshore wind farms play an important role. The available space combined with the more valuable wind conditions make offshore locations very attractive for wind powered energy production. In Europe a significant number of offshore wind farms already exist, especially in the North and Baltic Sea. In future this trend will continue, and further offshore wind farms will be built. The majority of offshore wind turbines are mounted on steel foundation structures. Due to the high-cyclic loading by wind and waves fatigue stress plays a substantial role regarding structural safety.
Besides the consideration of fatigue within the design process, to monitor existing steel structures for potential fatigue cracks during their life time is a major topic and a challenge.
For the structures of the offshore wind turbines are large and partially under water effective reliable methods for the detection of fatigue cracks are required.
This contribution presents investigations on different crack detection methods applied at high-cycle fatigue tests on small-scale welded steel samples as well as on large-scale welded steel components. The tests were conducted at the BAM laboratories. For crack detection mainly three different methods were used and compared. The first method regards to the measurement of strain by conventionally strain gauges. Secondly, the crack luminescence was used as a new and effective optical method for surface monitoring. And finally, crack detection by pressure differentials of the inner and outer section of tubular steel elements was investigated. A comparison study will emphasize the advantages and disadvantages of the different methods and show which of the described methods is potentially more suitable for an application on real offshore wind structures.
Damage detection and localization in civil or mechanical structures is a subject of active development and research. A few vibration‐based methods have been developed so far, requiring, for example, modal parameter estimates in the reference and damaged states of the investigated structure, and for localization in addition a finite element model. For structures in operation, temperature has been shown to be a major nuisance to the efficiency of such methods because the modal parameters are varying not only with damage but also due to temperature variations. For detection, a few rejection approaches have been developed. Besides the increased complexity, environmental variation is hardly taken into account in localization approaches. In this paper, we propose a sensitivity‐based correction of the identified modal parameters in the damaged state with respect to the temperature field in the reference state, on the basis of a sensitivity analysis with respect to temperature dependent Parameters of the finite element model in the reference state. The approach is then applied to the stochastic dynamic damage locating vector method, where its improved performance under nonuniform temperature variations is shown in a numerical application on a beam.
We examine the behavior of reinforced concrete components subjected to impact induced loading conditions which might be caused by vessels collisions such as aircraft fuel tanks The concrete plates were impact damaged at TU Dresden and shipped to BAM At BAM laminar tomography as the imaging method is used to determine and quantify the damage state An automatic crack detection method based on template matching is applied to find the cracks and we aim to develop a new method using machine learning Algorithms In addition numerical models are developed to understand the experiment and to predict the damage structures based on failure mechanisms.
The subject of damage localization is an important issue for Structural Health Monitoring (SHM) particularly in mechanical or civil structures under ambient excitation. In this paper, the statistical subspacebased damage localization method has been applied on a benchmark application, namely a 1/200 scale model of the Saint-Nazaire Bridge, which is a cable-stayed bridge located on the Loire River near the river’s mouth. The employed damage localization method combines data-driven features with physical parameter information from a finite element model in statistical tests, avoiding typical ill-conditioning problems of FE model updating. Damage is introduced in the mockup for cable failures on some of the 72 cables. The purpose of the experiment is to assess the capability of damage assessment methods to find a cable failure.
The Stochastic Dynamic Damage Locating Vector (SDDLV) approach is a vibration-based damage localization method based on both a finite element model of a structure and modal parameters estimated from output-only measurements in the damage and reference states. A statistical version of the Approach takes into account the inherent uncertainty due to noisy measurement data. In this paper, the effect of temperature fluctuations on the performance of the method is analyzed in a model-based approach using a finite element model with temperature dependent parameters. Robust damage localization is carried out by rejecting the temperature influence on the identified modal parameters in the damaged state. The algorithm is illustrated on a simulated structure.
Temperature variation can be a nuisance that perturbs vibration based structural health monitoring (SHM) approaches for civil engineering structures. In this paper, temperature affected vibration data is evaluated within a stochastic damage detection framework, which relies on a null space based residual. Besides two existing temperature rejection approaches – building a reference state from an averaging method or a piecewise method – a new approach is proposed, using model interpolation. In this approach, a general reference model is obtained from data in the reference state at several known reference temperatures. Then, for a particular tested temperature, a local reference model is derived from the general reference model. Thus, a well fitting reference null space for the formulation of a residual is available when new data is tested for damage detection at an arbitrary temperature. Particular attention is paid to the computation of the residual covariance, taking into account the uncertainty related to the null space matrix estimate. This improves the test performance, contrary to prior methods, for local and global damages, resulting in a higher probability of detection (PoD) for the new interpolation approach compared to previous approaches.
The subject of damage localization is an important issue for Structural Health Monitoring (SHM) particularly in mechanical or civil structures under ambient excitation. In this paper, the statistical subspacebased damage localization method has been applied on a benchmark application, namely a 1/200 scale model of the Saint-Nazaire Bridge, which is a cable-stayed bridge located on the Loire River near the river’s mouth. The employed damage localization method combines data-driven features with physical parameter information from a finite element model in statistical tests, avoiding typical ill-conditioning problems of FE model updating. Damage is introduced in the mockup for cable failures on some of the 72 cables. The purpose of the experiment is to assess the capability of damage assessment methods to find a cable failure.
The Stochastic Dynamic Damage Locating Vector (SDDLV) approach is a vibration-based damage localization method based on both a finite element model of a structure and modal parameters estimated
from output-only measurements in the damage and reference states. A statistical version of the Approach takes into account the inherent uncertainty due to noisy measurement data. In this paper, the effect of temperature fluctuations on the performance of the method is analyzed in a model-based approach using a finite element model with temperature dependent parameters. Robust damage localization is carried out by rejecting the temperature influence on the identified modal parameters in the damaged state. The algorithm is illustrated on a simulated structure.
Within the presented research project, experimental and numerical investigations were performed to develop a thin-shelled, modular, mobile element system made of a micro-reinforced ultra-high-performance ductile concrete (DUCON®). Material parameters were experimentally determined to adapt the material model within the numerical analysis applying the Drucker-Prager relationship. Afterwards, for validation of the numerical models, quasi-static and high-velocity impact tests were performed on plate-like structures. Finally, a suitable geometry of transportable barrier elements will be designed, which provides a maximum of resistance against impact by a minimum of weight and a maximum of mobility.
Risslumineszenz
(2018)
Unterraumbasierte Detektion von Strukturschäden an Jacket-Gründungen von Offshore-Windenergieanlagen
(2018)
Die vorliegende Arbeit beschreibt die Adaption eines globalen, schwingungsbasierten Verfahrens zur frühzeitigen Erkennung von Strukturschäden an Gründungsstrukturen offshore installierter Windenergieanlagen (OWEA). Damit soll es, Betreibern von Offshore-Windparks ermöglicht werden, im Rahmen periodisch durchgeführter messtechnischer Überwachungsmaßnahmen mit einem gegenüber wiederkehrender Inspektionen wesentlich geringen Aufwand auftretende Schäden an der Struktur zuverlässig zu delektieren.
Das untersuchte und implementierte Verfahren basiert auf der Methode der stochastischen unterraumbasierten Schadensdetektion. Dabei erfolgt eine statistische Analyse des wiederkehrend messtechnisch aufgenommenen dynamischen Antwortverhaltens des mechanischen Systems. Mittels statistischem Test werden signifikante Änderungen in dessen Eigenstruktur und damit Schäden delektiert.
Im Rahmen der vorliegenden Arbeit wurden umfangreiche experimentelle als auch numerische Untersuchungen zur Sensitivität und Robustheit des beschriebenen Schadensindikators durchgeführt. Dazu sind zunächst an einem Labormodell mittels künstlich und reversibel eingebrachter Schäden grundlegende Analysen zu den Einflüssen signal- und verfahrensinhärenter Kenngrößen durchgeführt worden. Auf der Basis dieser Ergebnisse wurde im Anschluss mittels numerischer Analysen das Antwortverhalten von OWEA simuliert und der entwickelte Algorithmus zur Schadensdetektion an den so realisierten Datensätzen angewendet.
Anhand der Ergebnisse der Arbeit wird aufgezeigt, dass, vorausgesetzt die Windenergieanlage befindet sich in Parkposition, eine Detektion von schon geringen Schäden an Gründungs-strukturen mit dem beschriebenen Verfahren, auch unter Einsatz weniger Messaufnehmer, zuverlässig möglich ist.
Unterraumbasierte Detektion von Strukturschäden an Jacket-Gründungen von Offshore-Windenergieanlagen
(2018)
Die vorliegende Arbeit beschreibt die Adaption eines globalen, schwingungsbasierten Verfahrens zur frühzeitigen Erkennung von Strukturschäden an Gründungsstrukturen offshore installierter Windenergieanlagen (OWEA). Damit soll es, Betreibern von Offshore-Windparks ermöglicht werden, im Rahmen periodisch durchgeführter messtechnischer Überwachungsmaßnahmen mit einem gegenüber wiederkehrender Inspektionen wesentlich geringen Aufwand auftretende Schäden an der Struktur zuverlässig zu delektieren.
Das untersuchte und implementierte Verfahren basiert auf der Methode der stochastischen unterraumbasierten Schadensdetektion. Dabei erfolgt eine statistische Analyse des wiederkehrend messtechnisch aufgenommenen dynamischen Antwortverhaltens des mechanischen Systems. Mittels statistischem Test werden signifikante Änderungen in dessen Eigenstruktur und damit Schäden delektiert.
Im Rahmen der vorliegenden Arbeit wurden umfangreiche experimentelle als auch numerische Untersuchungen zur Sensitivität und Robustheit des beschriebenen Schadensindikators durchgeführt. Dazu sind zunächst an einem Labormodell mittels künstlich und reversibel eingebrachter Schäden grundlegende Analysen zu den Einflüssen signal- und verfahrensinhärenter Kenngrößen durchgeführt worden. Auf der Basis dieser Ergebnisse wurde im Anschluss mittels numerischer Analysen das Antwortverhalten von OWEA simuliert und der entwickelte Algorithmus zur Schadensdetektion an den so realisierten Datensätzen angewendet.
Anhand der Ergebnisse der Arbeit wird aufgezeigt, dass, vorausgesetzt die Windenergieanlage befindet sich in Parkposition, eine Detektion von schon geringen Schäden an Gründungs-strukturen mit dem beschriebenen Verfahren, auch unter Einsatz weniger Messaufnehmer, zuverlässig möglich ist.
Within the presented research project, experimental and numerical investigations were performed to develop a thin-shelled, modular, mobile element system made of a micro-reinforced ultra-high-performance ductile concrete (DUCON®). Material parameters were experimentally determined to adapt the material model within the numerical analysis applying the Drucker-Prager relationship. Afterwards, for validation of the numerical models, quasi-static and high-velocity impact tests were performed on plate-like structures. Finally, a suitable geometry of transportable barrier elements will be designed, which provides a maximum of resistance against impact by a minimum of weight and a maximum of mobility.
Within the presented research project, experimental and numerical investigations were performed to develop a thin-shelled, modular, mobile element system made of a micro-reinforced ultra-high-performance ductile concrete (DUCON®). Material parameters were experimentally determined to adapt the material model within the numerical analysis applying the Drucker-Prager relationship. Afterwards, for validation of the numerical models, quasi-static and high-velocity impact tests were performed on plate-like structures. Finally, a suitable geometry of transportable barrier elements will be designed, which provides a maximum of resistance against impact by a minimum of weight and a maximum of mobility.
The local asymptotic approach is promising for vibration-based fault diagnosis when associated to a subspace-based residual function and efficient hypothesis testing tools. It has the ability of detecting small changes in some chosen system parameters. In the residual function,the left null space of the observability matrix associated to a reference model is confronted to the Hankel matrix of output covariances estimated from test data. When this left null space is not perfectly known from a model, it should be replaced by an estimate from data to avoid model errors in the residual computation. In this paper, the asymptotic distribution of the resulting data-driven residual is analyzed and its covariance is estimated, which includes also the covariance related to the reference null space estimate. The advantages of the data-driven residual are demonstrated in a numerical study, and the importance of including the covariance of the reference null space estimate is shown, which increases the detection Performance.
Right from the beginning of applying SHM to bridge structures it was obvious that environmental based perturbations on the measurement significantly influence the ability to identify structural damage.
Strategies are needed to classify such effects and consider them appropriately in SHM. Various methods have been developed and analyzed to separate environmental based effects from damage induced changes in the measures. Generally, two main approaches have emerged from research activity in this fields: (a) statistics based tools analyzing patterns in the data or in computed parameters and (b) methods, utilizing the structural model of the bridge taking into account environmental as well as damage based changes of stiffness values.
With the back-ground of increasing affordability of sensing and computing technology, effort should be made to increase sensitivity, reliability and robustness of procedures, separating environmental from damage caused changes in SHM measures. The contribution describes both general strategies and points out their Advantages and drawbacks. As basis, a review on relevant methods was conducted. The aim of the study is to classify approaches for separating damage describing information from environmental based perturbations in dependency of the SHM objective. And such, it is intended to describe a best practice in designing concepts for Monitoring infrastructure, naturally effected by environmental influences.
Automatic vibration-based structural health monitoring has been recognized as a useful alternative or addition to visual inspections or local non-destructive testing performed manually. It is, in particular, suitable for mechanical and aeronautical structures as well as on civil structures, including cultural heritage sites. The main challenge is to provide a robust damage diagnosis from the recorded vibration measurements, for which statistical signal processing methods are required. In this chapter, a damage detection method is presented that compares vibration measurements from the current system to a reference state in a hypothesis test, where data9
related uncertainties are taken into account. The computation of the test statistic on new measurements is straightforward and does not require a separate modal identification. The performance of the method is firstly shown on a steel frame structure in a laboratory experiment. Secondly, the application on real measurements on S101 Bridge is shown during a progressive damage test, where damage was successfully detected for different damage scenarios.
In structural parts under vibrational loading fatigue cracks can initiate and grow, which can lead to structural failure. Conventional non-destructive testing methods for crack detection provide just a snapshot of fatigue crack evolution, whereas crack luminescence coating realizes clear visibility of the entire crack formation. Fatigue causing cyclic tensile tests and examinations on special test bodies allowing control of the crack opening width demonstrate a high sensitivity of the coating.