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- Damage detection (6)
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In the last ten years, monitoring the integrity of the civil infrastructure has been an active research topic, including in connected areas as automatic control. It is common practice to perform damage detection by detecting changes in the modal parameters between a reference state and the current (possibly damaged) state from measured vibration data. Subspace methods enjoy some popularity in structural engineering, where large model orders have to be considered. In the context of detecting changes in the structural properties and the modal parameters linked to them, a subspace-based fault detection residual has been recently proposed and applied successfully, where the estimation of the modal parameters in the possibly damaged state is avoided. However, most works assume that the unmeasured ambient excitation properties during measurements of the structure in the reference and possibly damaged condition stay constant, which is hardly satisfied by any application. This paper addresses the problem of robustness of such fault detection methods. It is explained why current algorithms from literature fail when the excitation covariance changes and how they can be modified. Then, an efficient and fast subspace-based damage detection test is derived that is robust to changes in the excitation covariance but also to numerical instabilities that can arise easily in the computations. Three numerical applications show the efficiency of the new approach to better detect and separate different levels of damage even using a relatively low sample length.
The statistical subspace-based damage detection technique has shown promising theoretical and practical results for vibration-based structural health monitoring. It evaluates a subspacebased residual function with efficient hypothesis testing tools, and has the ability of detecting small changes in chosen system parameters. In the residual function, a Hankel matrix of Output covariances estimated from test data is confronted to its left null space associated to a reference model. The hypothesis test takes into account the covariance of the residual for decision making. Ideally, the reference model is assumed to be perfectly known without any uncertainty, which is not a realistic assumption. In practice, the left null space is usually estimated from a reference data set to avoid model errors in the residual computation. Then, the associated uncertainties may be non-negligible, in particular when the available reference data is of limited length. In this paper, it is investigated how the statistical distribution of the residual is affected when the reference null space is estimated. The asymptotic residual distribution is derived, where its refined covariance term considers also the uncertainty related to the reference null space estimate. The associated damage detection test closes a theoretical gap for real-world applications and leads to increased robustness of the method in practice. The importance of including the estimation uncertainty of the reference null space is shown in a numerical study
and on experimental data of a progressively damaged steel frame.
Im Dezember 2019 wurden bei einer turnusmäßigen Inspektion der B 1-Brücke am Altstädter Bahnhof in Brandenburg an der Havel massive und schnell voranschreitende Schäden festgestellt. Als Ursache für die Risse entlang der Längsträger wurde das Versagen eines signifikanten Anteils der Spanndrähte der konzentrierten Spannglieder vermutet. Die Brücke wurde umgehend für den Verkehr gesperrt und im Mai 2021 gesprengt. Im Vorfeld der Sprengung wurden durch das Bundesministerium für Digitales und Verkehr (BMDV) weiterführende Untersuchungen zum Schadensbild veranlasst, welche vom Landesbetrieb Straßenwesen Brandenburg koordiniert und in den Bauablauf integriert wurden. Das von der Hochschule für Technik und Wirtschaft (HTW) Dresden erstellte Versuchskonzept ist Bestandteil des vorangestellten ersten Teils des Beitrags [1]. Hier im zweiten Teil werden ausgewählte Ergebnisse der umfangreichen versuchsbegleitenden Mess- und Monitoringmaßnahmen beschrieben, welche in Kooperation der HTW Dresden, der Bilfinger Noell GmbH sowie der Bundesanstalt für Materialforschung und -prüfung (BAM) durchgeführt wurden.
Altematively to common modal analysis as tool for detectmg changes between a reference and an actual (possibly damaged) structural state, the subspace-based damage detection method has been developed in recent years and successfully adopted to test application data sets. Characteristic for that method is that instead of analyzing modal parameters, a Statistical test with respect to changes of a dynamic signature of structural response is introduced. Therefor, a Gaussian residual vector is extracted from the subspace of an output only Vibration data covariance matrix within the reference state. The paper describes the application of this damage detection method within a laboratory fatigue test on a Steel frame structure. Aim of the investigation was to analyze the usability and efficiency of the detection method for realistic damage on carrying structures of wind energy turbines. In a second Step, a numerical model of the lab test structure is developed and validated. Thus, a comparable numerical Simulation of the fatigue damage detection was feasible and the accuracy of the Simulation procedure could be verified. The present study describes the first Step in a two-step approach for quantifying and optimizing fundamental characteristics of SHM Systems for offshore wind turbine structures concerning a required number of sensors and their optimal location.
Subspace-based detection of fatigue damage on jacket support structures of offshore wind turbines
(2014)
The paper describes the application of the Stochastic Subspace-based Damage Detection (SSDD) method on model structures for an utilization of this approach on offshore wind turbine structures. Aim of the study was therefore to analyze the usability and efficiency of the detection method as well as to determine an optimized set of parameter for realistic damage on support structures of wind energy turbines. Based on results of an experimental fatigue test on a Steel frame laboratory structure a strategy for a numerical verification of the experimentally evolved damage detection was developed, utilizing a time integration approach to simulate the dynamic response. In a second Step the identified modeling and computing methodology is used to numerically investigate the ability to detect damage in real size structural components of offshore wind turbines.
Structural health monitoring with statistical methods during progressive damage test of S101 Bridge
(2014)
For the last decades vibration based damage detection of engineering structures has become an important issue for maintenance operations on transport infrastructure. Research in vibration based structural damage detection has been rapidly expanding from classic modal parameter estimation to modern operational monitoring. Since structures are subject to unknown ambient excitation in operation conditions, all estimates from the finite data measurements are of statistical nature. The intrinsic uncertainty due to finite data length, colored noise, non-stationary excitations, model order reduction or other operational influences needs to be considered for robust and automated structural health monitoring methods. In this paper, two subspace-based methods are considered that take these statistical uncertainties into account, first modal parameter and their confidence interval estimation for a direct comparison of the structural states, and second a statistical null space based damage detection test that completely avoids the identification step. The performance of both methods is evaluated on a large scale progressive damage test of a prestressed concrete road bridge, the S101 Bridge in Austria. In an on-site test, ambient vibration data of the S101 Bridge was recorded while different damage scenarios were introduced on the bridge as a benchmark for damage identification. It is shown that the proposed damage detection methodology is able to clearly indicate the presence of structural damage, if the damage leads to a change of the structural system.
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.
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.
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.
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.