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 - 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 - 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 -