TY - JOUR A1 - Marin, L. A1 - Döhler, Michael A1 - Bernal, D. A1 - Mevel, L. T1 - Robust statistical damage localization with stochastic load vectors N2 - The stochastic dynamic damage locating vector approach is a vibration-based damage localization method based on a finite element model of a structure and output-only measurements in both reference and damaged states. A stress field is computed for loads in the null space of a surrogate of the change in the transfer matrix at the sensor positions for some values in the Laplace domain. Then, the damage location is related to positions where the stress is close to zero. Robustness of the localization information can be achieved by aggregating results at different values in the Laplace domain. So far, this approach, and in particular the aggregation, is deterministic and does not take the uncertainty in the stress estimates into account. In this paper, the damage localization method is extended with a statistical framework. The uncertainty in the output-only measurements is propagated to the stress estimates at different values of the Laplace variable, and these estimates are aggregated based on statistical principles. The performance of the new statistical approach is demonstrated both in a numerical application and a lab experiment, showing a significant improvement of the robustness of the method due to the statistical evaluation of the localization information. KW - Damage localization KW - Load vectors KW - Ambient vibration KW - Covariance analysis KW - Subspace methods PY - 2015 UR - http://onlinelibrary.wiley.com/doi/10.1002/stc.1686/full U6 - https://doi.org/10.1002/stc.1686 SN - 1545-2255 SN - 1545-2263 VL - 22 IS - 3 SP - 557 EP - 573 PB - Wiley CY - Chichester AN - OPUS4-28069 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Döhler, Michael A1 - Luciano, M. A1 - Laurent, M. A1 - Dionisio, B. T1 - Statistical based decision making for damage localization with influence lines T2 - 9th International Workshop on Structural Health Monitoring CY - Stanford, CA, USA DA - 2013-09-10 PY - 2013 AN - OPUS4-29492 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Döhler, Michael A1 - Le Cam, V. A1 - Le Pen, M. A1 - Laurent, M. T1 - Embedded modal analysis algorithms on the smart wireless sensor platform PEGASE T2 - 9th International Workshop on Structural Health Monitoring CY - Stanford, CA, USA DA - 2013-09-10 PY - 2013 AN - OPUS4-29493 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Döhler, Michael A1 - Mevel, L. A1 - Hille, Falk T1 - Subspace-based damage detection under changes in the ambient excitation statistics N2 - 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. KW - Damage detection KW - Structural vibration monitoring KW - Ambient excitation KW - Subspace methods KW - Hypothesis testing PY - 2014 U6 - https://doi.org/10.1016/j.ymssp.2013.10.023 SN - 0888-3270 VL - 45 IS - 1 SP - 207 EP - 224 PB - Elsevier Ltd. CY - London AN - OPUS4-29899 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Döhler, Michael A1 - Hille, Falk A1 - Mevel, L. A1 - Rücker, Werner T1 - Estimation of modal parameters and their uncertainty bounds from subspace-based system identification PY - 2013 SN - 978-3-200-03179-1 IS - Chapter 5 SP - 91 EP - 106 CY - Vienna, Austria AN - OPUS4-29906 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Döhler, Michael A1 - Hille, Falk ED - Wicks, A. T1 - Subspace-based damage detection on steel frame structure under changing excitation N2 - Damage detection can be performed by detecting changes in the modal parameters between a reference state and the current (possibly damaged) state of a structure from measured output-only vibration data. Alternatively, a subspace-based damage detection test has been proposed and applied successfully, where changes in the modal parameters are detected, but the estimation of the modal parameters themselves is avoided. Like this, the test can run in an automated way directly on the vibration measurements. However, it was assumed 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. A new version of the test has been derived recently that is robust to such changes in the ambient excitation. In this paper, the robust test is recalled and its performance is evaluated both on numerical simulations and a real application, where a steel frame structure is artificially damaged in the lab. KW - Damage detection KW - Ambient vibration KW - Changing excitation KW - Subspace methods KW - Robust tests PY - 2014 SN - 978-3-319-04569-6 SN - 978-3-319-04570-2 U6 - https://doi.org/10.1007/978-3-319-04570-2_19 SN - 2191-5644 SN - 2191-5652 N1 - Serientitel: Conference Proceedings of the Society for Experimental Mechanics Series – Series title: Conference Proceedings of the Society for Experimental Mechanics Series VL - 5 SP - Chapter 19, 167 EP - 174 PB - Springer AN - OPUS4-31220 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Döhler, Michael A1 - Hille, Falk T1 - Subspace-based damage detection on steel frame structure under changing excitation T2 - 32nd IMAC, A Conference and Exposition on Structural Dynamics, 2014 CY - Orlando, FL, USA DA - 2014-02-03 PY - 2014 AN - OPUS4-31234 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Döhler, Michael A1 - Hille, Falk A1 - Mevel, L. A1 - Rücker, Werner T1 - Structural health monitoring with statistical methods during progressive damage test of S101 Bridge N2 - 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. KW - Subspace methods KW - Operational modal analysis KW - Uncertainty bounds KW - Damage detection KW - Prestressed concrete bridge PY - 2014 U6 - https://doi.org/10.1016/j.engstruct.2014.03.010 SN - 0141-0296 VL - 69 SP - 183 EP - 193 PB - Elsevier CY - Oxford AN - OPUS4-30665 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Döhler, Michael A1 - Mevel, L. A1 - Hille, Falk T1 - Efficient computation of minmax tests for fault isolation and their application to structural damage localization N2 - Fault detection and isolation can be handled by many different approaches. This paper builds upon a hypothesis test that checks whether the mean of a Gaussian random vector has become non-zero in the faulty state, based on a chi2 test. For fault isolation, it has to be decided which components in the parameter set of the Gaussian vector have changed, which is done by variants of the chi2 hypothesis test using the so-called sensitivity and minmax approaches. While only the sensitivity of the tested parameter component is taken into account in the sensitivity approach, the sensitivities of all parameters are used in the minmax approach, leading to better statistical properties at the expense of an increased computational burden. The computation of the respective test variable in the minmax test is cumbersome and may be ill-conditioned especially for large parameter sets, asking hence for a careful numerical evaluation. Furthermore, the fault isolation procedure requires the repetitive calculation of the test variable for each of the parameter components that are tested for a change, which may be a significant computational burden. In this paper, dealing with the minmax problem, we propose a new efficient computation for the test variables, which is based on a simultaneous QR decomposition for all parameters. Based on this scheme, we propose an efficient test computation for a large parameter set, leading to a decrease in the numerical complexity by one order of magnitude in the total number of parameters. Finally, we show how the minmax test is useful for structural damage localization, where an asymptotically Gaussian residual vector is computed from output-only vibration data of a mechanical or a civil structure. T2 - 19th World congress of the international federation of automatic control CY - Cape Town, South Africa DA - 24.08.2014 KW - Fault isolation KW - Residual evaluation KW - Statistical tests KW - Numerical computation KW - Mechanical systems PY - 2014 SP - 7382 EP - 7387 PB - IFAC AN - OPUS4-31573 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CHAP A1 - Döhler, Michael A1 - Hille, Falk A1 - Mevel, Laurent ED - Ottaviano, Erika ED - Pelliccio, Assunta ED - Gattulli, Vincenzo T1 - Vibration-based monitoring of civil structures with subspace-based damage detection N2 - 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. KW - Structural health monitoring KW - Subspace methods KW - Damage detection KW - Statistical tests KW - Vibrations PY - 2018 SN - 978-3-319-68645-5 U6 - https://doi.org/10.1007/978-3-319-68646-2 SP - 307 EP - 326 PB - Springer International Publishing CY - Cham ET - 1. AN - OPUS4-45127 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Marin, L. A1 - Döhler, Michael A1 - Bernal, D. A1 - Mevel, L. ED - Chang, F.-K. T1 - Statistical based decision making for damage localization with influence lines N2 - A theorem on damage localization from flexibility changes has been proven recently, where it has been shown that the image of the change in flexibility δF between damaged and reference states of a structure is a basis for the influence lines of stress resultants at the damaged locations. This damage localization approach can operate on output-only vibration measurements from damaged and reference states, and a finite element model of the structure in reference state is required. While the localization approach is based on purely mechanical principles, an estimate of the image of δF is required from the data that is subject to statistical uncertainty due to unknown noise excitation and finite data length. In this paper, this uncertainty is quantified from the measurements and a statistical framework is added for the decision about damaged elements. The combined approach is successfully applied to a numerical simulation and to a cantilever beam in a lab experiment. T2 - IWSHM 2013 - 9th International workshop on structural health monitoring CY - Stanford, CA, USA DA - 2013-09-10 PY - 2013 SN - 978-1-60595-115-7 VL - 1 SP - 159 EP - 166 AN - OPUS4-30476 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Le Cam, V. A1 - Döhler, Michael A1 - Le Pen, M. A1 - Mevel, L. ED - Chang, F.-K. T1 - Embedded modal analysis algorithms on the smart wireless sensor platform PEGASE N2 - Operational modal analysis and vibration based damage detection of engineering structures have become important issues for Structural Health Monitoring (SHM) and maintenance operations, e.g. on transport infrastructure. Methods from control engineering have been adopted and converted for the application on civil structures. Approaches like subspace-based system identification combine excellent theoretical properties under the unknown excitation properties of a structure with practical usefulness. In this paper, the implementation of covariance-driven stochastic subspace identification (SSI) on the smart wireless sensor platform PEGASE is described. Special care is taken about the fast implementation of this technique since the computations are embedded on the platform and perform in real-time. The most efficient and current version of subspace algorithms has been implemented. Efficiency and memory consumption are primary criteria in this implementation. First validated results will be given for each step of the algorithms: crosscorrelation on natural inputs signal from sensors; Hankel matrix output; SSI implementation using the LAPACK library to get a SVD, pseudo-inverse, eigenvalues etc. Results validation has been correlated between PEGASE implementation and the previous processing in static situation: the same data was collected by wired sensors and data-loggers, then, later, processed on a PC using traditional Matlab software. In parallel, from an engineering point of view, a description of the PEGASE wireless platform will be given: generic usage, wide capacities, embedded Digital Signal Processing (DSP) processor and Library over a small embedded Linux Operating System, a very accurate synchronization principle based on a GPS/PPS principle, etc. Perspectives about a complete technical in-situ installation will also be given. T2 - IWSHM 2013 - 9th International workshop on structural health monitoring CY - Stanford, CA, USA DA - 2013-09-10 PY - 2013 SN - 978-1-60595-115-7 VL - 1 SP - 1210 EP - 1217 AN - OPUS4-30477 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -