On the influence of sample length and measurement noise on the stochastic subspace damage detection technique

International audienceIn this paper the effects of measuring noise and number of samples is studied on the stochastic subspace damage detection (SSDD) technique. In this technique, i.e., SSDD, the need of evaluating the eigenstructure of the system is circumvented, making this approach capable of dealing with real-time measurements of structures. In previous studies, the effect of these practical parameters was examined on simulated measurements from a model of a real structure. In this study, these effects are formulated for the expected damage index evaluated from a Chi-square distributed value. Several theorems are proposed and proved. These theorems are used to develop a guideline to serve the user of the SSDD method to face these effects

Minimum detectable damage for stochastic subspace-based methods

International audienceDetecting small and local damages on structures based on ambient vibrations is a major challenge in structural health monitoring. However, being able to identify the minimum damage is essential for quantifying the effectiveness of the instrumentation and for defining the limitations of low-frequency vibration monitoring in general. This paper shows how subspace-based methods could be used by engineers to predict the minimum damage that can be detected. The method employs a Gaussian subspace-based residual vector as a damage-sensitive criterion and evaluates its deviation from zero mean through two different statistical hypothesis tests, a parametric version and a non-parametric one. A sensitivity analysis is carried out to parametrize the deviation from the nominal state, and link it to physical parameters in a finite element model through the Fisher information matrix. This link can also be used to predict the minimum detectable damage, e.g. by prescribing a minimum probability of detection based on code-based reliability concepts. Ultimately, the developed theory is verified by means of a numerical example

Subspace based damage detection technique: investigation on the effect of number of samples

International audienceDamage detection techniques are the main tool in health monitoring to assess the functionality of structures. Among these techniques, statistical subspace-based damage detection technique is a robust method to evaluate the conditions of a structure without the need of evaluating its modal parameters. This can circumvent all the errors and difficulties in evaluating the modal properties of the structure while the changes in the eigen-structure of the data is identified indirectly. In our previous studies, the effects of damage location, damage ratio, and the noise in the data were investigated. In this study, the sensitivity of this technique to the number of samples of the data is addressed. The interaction of the number of measurements with damage and noise ratio is also investigated. For this purpose a bridge structure located in Reibersdorf, Austria, is considered. This structure is modelled and calibrated to the real test data; subsequently the damage is modelled in one of the elements for different damage ratios and excitation duration. It was demonstrated that this technique can operate robustly even with high noise present in the data by acquiring typical number of measurements especially for reference state data. Moreover, it was concluded that if the length of the reference data would not be large enough, increasing the length of the test data cannot much help in identifying the damage in the structure

Robust statistical subspace-based damage assessment

The rapid spread and increasing affordability of sensors, are encouraging the government and stake-holders to instrument important infra-structures and structures. These sensors generate vast amount of data which can be used in real-time health monitoring of the instrumented structures by using damage identification methods. A significant component of structural health monitoring is damage identification methods which process the data with the purpose of detecting damages in the structures. One of these methods with a theoretical background is the statistical subspace damage identification method (SSDI). The overarching goal in this thesis is to close the gap between theory and practice, in order to have a method with a strong theoretical background and a credible applicability at the same time. In order to achieve this goal several contributions are motivated in this thesis, which are presented as follows: Firstly, the effect of two challenges faced in the damage detection of structures under real test conditions, namely the measurement noise and duration (length), are theoretically evaluated. It is demonstrated that the measurement noise and length have considerable influence on the statistical subspace damage detection method and they need to be considered based on these proposed theories. Secondly, the statistical subspace damage localization (SSDL) method, is assessed for the first time, in localizing the damage of a real experimental structure, i.e. the Yellow frame, established on the course of this research at UBC. Several methods and theories are developed in order to enable this method in identifying the damage under real test conditions. It was demonstrated that by employing the proposed theories, the SSDL method can robustly locate the damage in a real structure such as the Yellow frame. Finally, two indexes are proposed in predicting the detectability of damage in each element of a structure. These indexes provide valuable information on the sensitivity of SSDL method to the damage in each element. All the proposed theories and methods are demonstrated theoretically; subsequently, they are verified by simple and sophisticated analytical models, and finally, they are validated by real-test data.Applied Science, Faculty ofCivil Engineering, Department ofGraduat

Damage localization of a real structure using the statistical subspace damage localization method

International audienceIn this paper the statistical subspace damage localization (SSDL) method is employed in localizing the damage in a real structure, namely the Yellow frame. The SSDL method is developed for real testing conditions and tested in two damage configurations. It was demonstrated that the SSDL method can localize the damage robustly in the Yellow frame for simple and multiple distinct damage scenarios using the analytical modal parameters. The method is described and its effectiveness is demonstrated

Classification of Benign and Malignant Breast Tumors by 2-D Analysis Based on Contour Description and Scatterer Characterization

Ultrasound B-mode scanning based on the echo intensity has become an important clinical tool for routine breast screening. The efficacy of the Nakagami parametric image based on the distribution of the backscattered signals for quantifying properties of breast tissue was recently evaluated . The B-mode and Nakagami images reflect different physical characteristic of breast tumors: the former describes the contour features, and the latter reflects the scatterer arrangement inside a tumor. The functional complementation of these two images encouraged us to propose a novel method of 2-D analysis based on describing the contour using the B-mode image and the scatterer properties using the Nakagami image, which may provide useful clues for classifying benign and malignant tumors. To validate this concept, raw data were acquired from 60 clinical cases, and five contour feature parameters (tumor circularity, standard deviation of the normalized radial length, area ratio, roughness index, and standard deviation of the shortest distance) and the Nakagami parameters of benign and malignant tumors were calculated. The receiver operating characteristic curve and fuzzy c-means clustering were used to evaluate the performances of combining the parameters in classifying tumors. The clinical results demonstrated the presence of a tradeoff between the sensitivity and specificity when either using a single parameter or combining two contour parameters to discriminate between benign and malignant cases. However, combining the contour parameters and the Nakagami parameter produces sensitivity and specificity that simultaneously exceed 80%, which means that the functional complementation from the B-scan and the Nakagami image indeed enhances the performance in diagnosing breast tumors

Investigation on the sensitivity of subspace based damage detection technique to damage and noise levels

International audienceDamage detection techniques are one of the main tools in health monitoring of structures. This paper addresses the effect of noise in the measured data on a robust damage detection method, namely statistical subspace-based damage detection technique. In this method the need of evaluating the modal parameters of the structure is circumvented which makes this method capable in real-time monitoring of structures. Moreover, this method identifies the changes in the eigen-structure of the model which makes it a robust approach to function with high amount of noise in the input data. In order to investigate the effect of noise on this method, a bridge structure located in Reibersdorf, Austria, is considered. This structure is modeled and calibrated to the real test data; subsequently the damage is modeled in one of the elements for different damage ratios. With using white noise excitation, ambient vibration test data is simulated and different noise ratios are applied to the data. A reference state of the structure is evaluated using this technique. A subspace-based residual between the reference and possibly damaged states is defined independently from the input excitations employing a ߯ ଶ test and then is compared to a threshold corresponding to the reference state. Subsequently, the effect of noise ratios in the reference state and the measured data and their difference is investigated. It was concluded that the SSDD technique is capable of estimating the damage in almost all damage ratios and even for high noise ratios in the data. Moreover, it was observed that the noise ratio difference in the reference state and measured data may be interpreted as damage, since it is reflected in the computed residual. An optimum range of the noise in the data is also assessed and proposed

Sensitivity Evaluation of Subspace-based Damage Detection Method to Different Types of Damage

International audienceIn this paper we investigate a damage detection technique based on the subspace method by applying it to an existing bridge structure model. A reference state of the structure is evaluated using this technique and subsequently its modal parameters are indirectly compared to the current state of the structure. There are no modal parameters estimated in this method. A subspace-based residual between the reference and possibly damaged states is defined independently from the input excitations employing a chi2 test and then is compared to a threshold corresponding to the reference state. This technique is applied to a model of the bridge structure located in Reibersdorf, Austria. The structure is excited randomly with white noise at different locations and the output data is generated at typical locations instrumented and measured in a bridge. Various damages are simulated in different elements and the sensitivity of the method to each type and ratio of damages is assessed. This evaluation is performed by comparing the prediction of the damage state using this technique and the simulated damage of the structure. It can be inferred from the results that in general the statistical subspace-based damage detection technique recognizes most of the damage cases, except the ones with insignificant change in the global dynamic behaviour

Output-only damage diagnosis for plan-symmetric buildings with asymmetric damage using modal flexibility-based deflections

Effective methods for vibration-based damage diagnosis in building structures are based on the estimation of structural deflections from identified modal flexibility (MF) matrices. However, most of the existing methods and previous studies that use MF-based deflections were developed by considering the case of buildings that can be modeled as planar structures (e.g. plan-symmetric buildings) both in the baseline and possibly damaged states. In an attempt to fill this research gap, a deflection-based method for output-only damage diagnosis in building structures tested under ambient vibrations is proposed in this paper. The method is applicable for simple rectangular plan-symmetric \u201cbox type\u201d 3D building structures which may experience asymmetric damage, and it can be used for detecting, localizing and quantifying the damage. One of the main differences between the proposed and the existing methods is related to the inspection loads adopted to estimate the MF-based deflections. The inspection loads of the proposed method are more complex than the uniform translational loads adopted in the existing methods. Such proposed loads in fact can be assembled only after having estimated the position of the center of stiffness for each story of the structure. According to the proposed approach, the locations of the centers of stiffness are extracted from the experimentally-derived modal flexibility matrices, before performing the damage diagnosis process. The effectiveness and validity of the proposed method was demonstrated both through numerical analyses and by executing experimental ambient vibration tests on a frame building. The results of the proposed method were also compared with the existing approach which was developed for planar structures. This comparison (made both through numerical and experimental analyses) demonstrated that only the proposed approach can be used to perform a correct damage diagnosis process in plan-symmetric buildings which may experience asymmetric damage, especially when considering the damage quantification problem

Transfer matrices-based output-only statistical damage localization and quantification on a frame structure

International audienceDamage localization in civil or mechanical structures is a subject of active development and research. In this paper, vibration measurements and a finite element model are used to locate loss of stiffness in a steel frame structure at the University of British Columbia. Damage localization is not very well developed so far and few methods show promising properties in practice. Among them, the Stochastic Dynamic Damage Locating Vector (SDDLV) approach has interesting capabilities. In this paper, it is compared to a sensitivity based approach developed by the authors. Both approaches have in common to be built on the estimated transfer matrix difference between reference and damaged states. Both methods are tested for localization and quantification on the Yellow Frame structure at the University of British Columbia