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 - 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 - Mevel, L. A1 - Döhler, Michael T1 - Subspace methods for blind identification of structural dynamics T2 - Colloquium Rennais des Sciences du Numerique CY - Rennes, France DA - 2013-04-17 PY - 2013 AN - OPUS4-28068 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Döhler, M. A1 - Hille, Falk A1 - Mevel, L. A1 - Rücker, Werner ED - Chang, F.-K. T1 - Structural health monitoring during progressive damage test of S101 bridge N2 - For the last decades vibration based identification of damage on civil Engineering structures has become an important issue for maintenance operations on transport infrastructure. Research in that field has been rapidly expanding from classic modal Parameter estimation using measured excitation to modern operational monitoring. Here the difficulty is to regard to the specific environmental and operational influence to the structure under observation. In this paper, two methods accounting for statistical and/or operational uncertainties are applied to measurement data of a progressive damage test on a prestressed concrete bridge. On the base of covariance driven Stochastic Subspace Identification (SSI) an algorithm is developed to monitor and automatically compute confidence intervals of the obtained modal parameters. Furthermore, a null space based non-parametric damage detection method, utilizing a statistical χ2 type test is applied to the measurement data. It can be shown that for concrete bridges the proposed methodology is able to clearly indicate the presence of structural damage, if the damage leads to a change of the structural system. T2 - 8th International workshop on structural health monitoring 2011 CY - Stanford, CA, USA DA - 13.09.2011 KW - Subspace identification KW - Damage detection KW - Convidence intervals KW - Prestressed concrete bridge PY - 2011 SN - 978-1-60595-053-2 VL - 1 SP - 748 EP - 758 PB - DEStech Publications, Inc. AN - OPUS4-24688 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hille, Falk A1 - Döhler, M. A1 - Mevel, L. A1 - Rücker, Werner ED - De Roeck, G. ED - Degrande, G. ED - Lombaert, G. ED - Müller, G. T1 - Subspace-based damage detection methods on a prestressed concrete 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. Methodologies from control Engineering especially of aerospace applications have been adopted and converted for the application on civil structures. Here the difficulty is to regard to the specific environmental and operational influence to the structure under observation. A null space based damage detection algorithm is tested for its sensitivity to structural damage of a prestressed concrete road bridge. Specific techniques and extensions of the algorithm are used to overcome difficulties from the size of the structure which is associated with the number of recorded sensor channels as well as from the operational disturbances by a nearby construction site. It can be shown that for concrete bridges the proposed damage detection methodology is able to clearly indicate the presence of structural damage, if the damage leads to a significant change of the structural system. Small damage which do not result in a System change when not activated by loading, do not lead to a modification of the dynamic response behavior and for that cannot be detected with the proposed global monitoring method. T2 - EURODYN 2011 - 8th International conference on structural dynamics CY - Leuven, Belgium DA - 04.07.2011 KW - Subspace methods KW - Fault detection KW - Monitoring techniques KW - Concrete bridge PY - 2011 SN - 978-90-760-1931-4 IS - MS12 TUE 11:45 SP - 2304 EP - 2310 AN - OPUS4-24689 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Döhler, M. A1 - Hille, Falk A1 - Lam, X.-B. A1 - Mevel, L. A1 - Rücker, Werner ED - Proulx, T. T1 - Confidence intervals of modal parameters during progressive damage test N2 - In Operational Modal Analysis, the modal parameters (natural frequencies, damping ratios and mode shapes) obtained from Stochastic Subspace Identification (SSI) of a structure, are afflicted with statistical uncertainty. For evaluating the quality of the obtained results it is essential to know the respective confidence intervals of these figures. In this paper we present algorithms that automatically compute the confidence intervals of modal parameters obtained from covarianceand data-driven SSI of a structure based on vibration measurements. They are applied to the monitoring of the modal parameters of a prestressed concrete highway bridge during a progressive damage test that was accomplished within the European research project IRIS. Results of the covariance- and data-driven SSI are compared. T2 - 29th IMAC - Conference on structural dynamics CY - Jacksonville, FL, USA DA - 31.01.2011 KW - Stochastische subspace basierte Identifikation KW - Schadensdetektion KW - Spannbetonbrücke PY - 2011 SN - 978-1-4419-9304-5 U6 - https://doi.org/10.1007/978-1-4419-9305-2_17 SN - 2191-5644 N1 - Serientitel: Conference Proceedings of the Society for Experimental Mechanics Series – Series title: Conference Proceedings of the Society for Experimental Mechanics Series VL - 4 SP - 237 EP - 250 PB - Springer AN - OPUS4-24335 LA - eng 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 - JOUR A1 - Viefhues, Eva A1 - Döhler, M. A1 - Hille, Falk A1 - Mevel, L. T1 - Statistical subspace-based damage detection with estimated reference N2 - 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. KW - Damage detection KW - Uncertainty quantification KW - Statistical tests KW - Ambient excitation KW - Vibration measurement PY - 2022 U6 - https://doi.org/10.1016/j.ymssp.2021.108241 SN - 0888-3270 VL - 164 SP - 108241 PB - Elsevier Ltd. AN - OPUS4-52998 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Viefhues, Eva A1 - Döhler, M. A1 - Simon, Patrick A1 - Herrmann, Ralf A1 - Hille, Falk A1 - Mevel, L. ED - Cunha, A. ED - Caetano, E. T1 - Stochastic subspace-based damage detection of a temperature affected beam structure N2 - Structural health monitoring (SHM) of civil structures often is limited due to changing environmental conditions, as those changes affect the structural dynamical properties in a similar way like damages can do. In this article, an approach for damage detection under changing temperatures is presentedand applied to a beam structure. The used stochastic subspace-based algorithm relies on a reference null space estimate, which is confronted to data from the testing state in a residual function. For damage detection the residual is evaluated by means of statistical hypothesis tests. Changes of the system due to temperature effects are handled with a model interpolation approach from linear parameter varying system theory. From vibration data measured in the undamaged state at some few reference temperatures, a model of the dynamic system valid for the current testing temperature is interpolated. The reference null space and the covariance matrix for the hypothesis test is computed from this interpolated model. This approach has been developed recently and was validated in an academic test case on simulations of a mass-spring-damper. In this paper, the approach is validated experimentally on a beam structure under varying temperature conditions in a climate chamber. Compared to other approaches, the interpolation approach leads to significantly less false positive alarms in the reference state when the structure is exposed to different temperatures, while faults can still be detected reliably. T2 - 10th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 10 CY - Online meeting DA - 30.06.2021 KW - Damage detection KW - Subspace methods KW - Temperature effects KW - Model interpolation KW - Climate chamber KW - Laboratory beam structure PY - 2021 SP - 1 EP - 6 AN - OPUS4-52999 LA - eng 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 - CONF A1 - Bhuyan, Md Delwar Hossain A1 - Le Touz, N. A1 - Gautier, G. A1 - Döhler, M. A1 - Hille, Falk A1 - Dumoulin, J. A1 - Mevel, L. T1 - Load vector based damage localization with rejection of the temperature effect N2 - 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. T2 - 8. International Operational Modal Analysis Conference CY - Kopenhagen, Denmark DA - 12. Mai 2019 KW - SDDLV KW - Load vector KW - Temperature rejection KW - Statistical evaluation PY - 2019 SP - 1 EP - 10 AN - OPUS4-48182 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bhuyan, Md Delwar Hossain A1 - Döhler, M. A1 - Lecieux, Y. A1 - Lupi, C. A1 - Thomas, J.-C. A1 - Schoefs, F. A1 - Hille, Falk A1 - Mevel, L. T1 - Statistical subspace based damage localization on Saint-Nazaire bridge mock-up N2 - 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. T2 - 8. International Operational Modal Analysis Conference CY - Kopenhagen, Denmark DA - 12. Mai 2019 KW - Damage localization KW - Cable-stayed bridge KW - Cable failure KW - Structural health monitoring PY - 2019 SP - 1 EP - 9 AN - OPUS4-48183 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Viefhues, Eva A1 - Döhler, M. A1 - Zhang, Q. A1 - Hille, Falk A1 - Mevel, L. T1 - Subspace-based Damage Detection with Rejection of the Temperature Effect and Uncertainty in the Reference N2 - 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. T2 - International Operational Modal Analysis Conference CY - Copenhagen, Danmark DA - 13.05.2019 KW - Uncertainty KW - Statistical method KW - Subspace-based method KW - Temperature rejection KW - Model interpolation PY - 2019 SP - 1 EP - 11 AN - OPUS4-48240 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bhuyan, Md Delwar Hossain A1 - Le Touz, N. A1 - Gautier, G. A1 - Döhler, M. A1 - Hille, Falk A1 - Dumoulin, J. A1 - Mevel, L. T1 - Load Vector Based Damage Localization with Rejection of the Temperature Effect N2 - 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. T2 - International Operational Modal Analysis Conference CY - Copenhagen, Danmark DA - 13.05.2019 KW - Statistical evaluation KW - Damage localization KW - SDDLV KW - Load vector KW - Temperature rejection PY - 2019 SP - 1 EP - 10 AN - OPUS4-48241 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bhuyan, Md Delwar Hossain A1 - Döhler, M. A1 - Lecieux, Y. A1 - Lupi, C. A1 - Thomas, J. A1 - Schoefs, F. A1 - Hille, Falk A1 - Mevel, L. T1 - Statistical Subspace-based Damage Localization on Saint-Nazaire Bridge Mock-Up N2 - 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. T2 - International Operational Modal Analysis Conference CY - Copenhagen, Danmark DA - 13.05.2019 KW - Structural health monitoring KW - Damage localization KW - Cable-stayed bridge KW - Cable failure PY - 2019 SP - 1 EP - 9 AN - OPUS4-48243 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 - TY - CONF A1 - Baeßler, Matthias A1 - Bhuyan, Delwar A1 - Hille, Falk A1 - Viefhues, Eva A1 - Döhler, M. A1 - Mevel, L. ED - Zingoni, Alphose T1 - Impact of environmental based effects on SHM strategies N2 - 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. T2 - SEMC 2019 CY - Cape Town, South Africa DA - 02.09.2019 KW - SHM environmental bridges PY - 2019 SN - 978-1-138-38696-9 SN - 978-0-429-42650-6 U6 - https://doi.org/10.1201/9780429426506 SP - Paper 324, 1 EP - Paper 324, 6 PB - CRC Press CY - Boca Raton AN - OPUS4-49167 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Bhuyan, Md Delwar Hossain A1 - Gautier, G. A1 - Le Touz, N. A1 - Döhler, M. A1 - Hille, Falk A1 - Dumoulin, J. A1 - Mevel, L. T1 - Vibration‐based damage localization with load vectors under temperature changes N2 - 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. KW - Statistical evaluation KW - Damage localization KW - Load vector KW - Temperature effect rejection KW - Temperature modeling PY - 2019 U6 - https://doi.org/10.1002/stc.2439 SN - 1545-2255 SN - 1545-2263 SP - e2439, 1 EP - 16 PB - John Wiley & Sons, Ltd. AN - OPUS4-48843 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -