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A pattern recognition approach for damage detection and temperature compensation in acousto-ultrasonics 7

A pattern recognition approach for damage detection and temp...

引用

7th European Workshop on Structural Health Monitoring, EWSHM 2014

作者： Torres-Arredondo, M.-A. Sierra-Pérez, Julián Zenuni, Erion Cabanes, Guénaël Rodellar, José Güemes, Alfredo Fritzen, C.-P. Augsburg Germany Grupo de Investigación en Ingeniería Aeroespacial Universidad Pontificia Bolivariana Medellín Colombia Department of Aerospace Materials and Processes Universidad Politécnica de Madrid Spain University of Siegen Institute of Mechanics and Control Engineering-Mechatronics Siegen Germany University of Paris 13 Institut Galilée LIPN CNRS France Department of Applied Mathematics III Universitat Politècnica de Catalunya-BarcelonaTech Barcelona Spain Germany

the global trends in the construction of modern structures require the integration of sensors together with data recording and analysis modules so that their integrity can be continuously monitored for safe-life, economic and ecological reasons. this process of measuring and analysing the data from a distributed sensor network all over a structural system in order to quantify its condition is known as structural health monitoring (SHM). Guided ultrasonic wave-based techniques are increasingly being adapted and used in several SHM systems which benefit from built-in transduction, large inspection ranges, and high sensitivity to small flaws. However, for reliable health monitoring, much information regarding the innate characteristics of the sources and their propagation is essential. Moreover, any SHM system which is expected to transition to field operation must take into account the influence of environmental and operational changes which cause modifications in the stiffness and damping of the structure and consequently modify its dynamic behaviour. On that account, special attention is paid in this paper to the development of an efficient SHM methodology where robust signal processing and pattern recognition techniques are integrated for the correct interpretation of complex ultrasonic waves within the context of damage detection and identification. the methodology is based on an acousto-ultrasonics technique where the discrete wavelet transform is evaluated for feature extraction and selection, linear principal component analysis for data-driven modelling and selforganizing maps for a two-level clustering under the principle of local density. At the end, the methodology is experimentally demonstrated and results show that all the damages were detectable and identifiable. Copyright © Inria (2014).

关键词： Damage detection

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small object detection via fast discrete Curvelet transform

Small object detection via fast discrete Curvelet transform

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25th SPIE conference on signal and data processing of small targets

作者： Valdez, Hector A. Lu, thomas T. Chao, Tien-Hsin Calif State Univ Long Beach Long Beach CA 90840 USA CALTECH Jet Prop Lab 4800 Oak Grove Dr Pasadena CA 91125 USA

ISBN: (纸本)9780819497079

this paper describes the Fast Discrete Curvelet Transform (FDCT) which is integrated into an automated object detection framework capable of fast image processing for the purpose of tracking multiple objects of interest. the distinguishing difference between FDCT and other transforms is that the Curvelet coefficients have three beneficial parameters, which define scale, orientation, and spatial locations. We utilize these parameters to efficiently detect relatively small objects in a variety of image and video data sets. We have implemented the FDCT in a multi-stage automatic target recognition (ATR) architecture. the results of the current algorithm yield a highly sensitive detection of small targets in noisy backgrounds.

关键词： ATR Curvelet object detection ROI sparse representation targeting

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An Examination of the Application of Space Time Adaptive processing for the Detection of Maritime Surface targets from High Altitude Airborne Platforms

An Examination of the Application of Space Time Adaptive Pro...

引用

25th SPIE conference on signal and data processing of small targets

作者： McDonald, Michael Cerutti-Maori, Delphine Def R&D Canada 3701 Carling Ave Ottawa ON Canada Fraunhofer FHR D-53343 Wachtberg Germany

ISBN: (纸本)9780819497079

An examination of the application of Space Time Adaptive processing (STAP) techniques to real, multi-channel, medium grazing angle, radar sea clutter data is undertaken and the detection performance is quantified against simulated moving maritime surface targets. the application of sub-optimal STAP approaches to the maritime radar detection problem is shown to be complicated by non-stationarity of sea clutter and rapid variations of the sea clutter spectrum due to transient wave activity. Observed performance gains from maritime STAP are much more limited than those observed for Ground Moving Target Indication (GMTI) due to the inherent spectral width of sea clutter and the slow Doppler velocities of maritime targets. three sub-optimal STAP processing architectures are examined and PRI-Staggered Post-Doppler is shown to provide consistently superior detection performance for the data set in question.

关键词： Maritime surveillance STAP Radar GMTI

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Identification of Human Motion Signature using Airborne Radar data

Identification of Human Motion Signature using Airborne Rada...

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25th SPIE conference on signal and data processing of small targets

作者： McDonald, Michael Damini, Anthony Def R&D Canada Ottawa ON Canada

ISBN: (纸本)9780819497079

data containing the radar signature of amoving person on the ground were collected at ranges of up to 30 km from a moving airborne platform using the DRDC Ottawa X-band Wideband Experimental Airborne Radar (XWEAR). the human target radar echo returns were found to possess a characteristic amplitude modulated (AM) and frequency modulated (FM) signature which could be usefully characterized in terms of conventional AM and FM modulation parameters. Human detection performance after space time adaptive processing is frequently limited by false alarms arising from incomplete cancellation of large radar cross-section discretes during the whitening step. However, the clutter discretes possess different modulation characteristics from the human targets discussed above. the ability of pattern classification techniques to use this parameter measurement space to distinguish between human targets and clutter discretes is explored and preliminary results presented.

关键词： STAP Radar GMTI

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Detection of unusual trajectories using multi-objective evolutionary algorithms and rough sets

Detection of unusual trajectories using multi-objective evol...

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25th SPIE conference on signal and data processing of small targets

作者： Smolinski, Tomasz G. Newell, Trevor McDaniel, Samantha Pokrajac, David Delaware State Univ Dept Comp & Informat Sci Dover DE 19901 USA

ISBN: (纸本)9780819497079

Detection of unusual trajectories of moving objects (e.g., people, automobiles, etc.) is an important problem in many civilian and military surveillance applications. In this work, we propose a multi-objective evolutionary algorithms and rough sets-based approach that breaks down 2-dimensional trajectories into a set of additive components, which then can be used to build a classifier capable of recognizing typical, but yet unseen trajectories, and identifying those that seem suspicious.

关键词： Detection of Unusual Trajectories data Mining Evolutionary Algorithms Rough Sets

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Particle Filter Tracking for the Banana Problem

Particle Filter Tracking for the Banana Problem

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25th SPIE conference on signal and data processing of small targets

作者： Romeo, Kevin Willett, Peter Bar-Shalom, Yaakov Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)9780819497079

In this paper we present an approach for tracking with a high-bandwidth active sensor in very long range scenarios. We show that in these scenarios the extended Kalman filter is not desirable as it suffers from major consistency problems;and most flavors of particle filter suffer from a loss of diversity among particles after resampling. this leads to sample impoverishment and the divergence of the filter. In the scenarios studied, this loss of diversity can be attributed to the very low process noise. However, a regularized particle filter is shown to avoid this diversity problem while producing consistent results. the regularization is accomplished using a modified version of the Epanechnikov kernel.

关键词： Particles Particle filters Detection and tracking algorithms Filtering (signal processing) Gaussian filters Digital filtering Error analysis Sensors Active sensors Statistical analysis

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On Covariance Structure in Noisy, Big data

On Covariance Structure in Noisy, Big Data

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25th SPIE conference on signal and data processing of small targets

作者： Paffenroth, Randy C. Nong, Ryan Du Toit, Philip C. Numerica Corp Loveland CO 80538 USA

ISBN: (纸本)9780819497079

Herein we describe theory and algorithms for detecting covariance structures in large, noisy data sets. Our work uses ideas from matrix completion and robust principal component analysis to detect the presence of low-rank covariance matrices, even when the data is noisy, distorted by large corruptions, and only partially observed. In fact, the ability to handle partial observations combined with ideas from randomized algorithms for matrix decomposition enables us to produce asymptotically fast algorithms. Herein we will provide numerical demonstrations of the methods and their convergence properties. While such methods have applicability to many problems, including mathematical finance, crime analysis, and other large- scale sensor fusion problems, our inspiration arises from applying these methods in the context of cyber network intrusion detection.

关键词： Sensors Matrices Computer networks Algorithms Computer intrusion detection Optimization (mathematics) Principal component analysis Sensor fusion data fusion Veins

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Feasibility Study on Service-based data Acquisition for Human signal Molecule Profiling database

Feasibility Study on Service-based Data Acquisition for Huma...

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IEEE 13th International conference on Bioinformatics and Bioengineering (BIBE)

作者： Zhao, Xinyan Dong, Tao Vestfold Univ Coll Dept Micro Nano Syst Technol IMST TekMar Borre Norway

ISBN: (纸本)9781479931637

A service-based model of human signal-molecule-profiling database (HSMPD) was proposed to prompt data acquisition of medical information from blood tests in traditional healthcare systems and to make the data be naturally converted into Health IT (HIT) services through the translational bioinformatics (TBI) community. A self-motivated mechanism to minimize the project investment was designed. the low-cost tool, called 'SMP chip', will be employed in blood tests inside hospitals, which results could be decoded and stored in HSMPD automatically. Successively, HIT services derived from HSMPD will provide a stable income to support the data acquisition processes. To explore the feasibility of the model, a small-scale survey study was performed in a common hospital. the positive results indicated that the cooperation of IT, engineering, healthcare systems and TBI community could provide a self-motivated solution to build the HSMPD platform.

关键词： bioinformatics data acquisition database management systems health care hospitals

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A Minimalist Approach to Bias Estimation for Passive Sensor Measurements with targets of Opportunity

A Minimalist Approach to Bias Estimation for Passive Sensor ...

引用

25th SPIE conference on signal and data processing of small targets

作者： Belfadel, Djedjiga Osborne, Richard W., III Bar-Shalom, Yaakov Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)9780819497079

In order to carry out data fusion, registration error correction is crucial in multisensor systems. this requires estimation of the sensor measurement biases. It is important to correct for these bias errors so that the multiple sensor measurements and/or tracks can be referenced as accurately as possible to a common tracking coordinate system. this paper provides a solution for bias estimation for the minimum number of passive sensors (two), when only targets of opportunity are available. the sensor measurements are assumed time-coincident (synchronous) and perfectly associated. Since these sensors provide only line of sight (LOS) measurements, the formation of a single composite Cartesian measurement obtained from fusing the LOS measurements from different sensors is needed to avoid the need for nonlinear filtering. We evaluate the Cramer-Rao Lower Bound (CRLB) on the covariance of the bias estimate, i.e., the quantification of the available information about the biases. Statistical tests on the results of simulations show that this method is statistically efficient, even for small sample sizes (as few as two sensors and six points on the trajectory of a single target of opportunity). We also show that the RMS position error is significantly improved with bias estimation compared with the target position estimation using the original biased measurements.

关键词： Bias estimation bias observability statistical efficiency CRLB composite measurements maximum likelihood

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Human Segmentation and Pose Recognition in Fish-eye Video for Assistive Environments

Human Segmentation and Pose Recognition in Fish-eye Video fo...

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IEEE 13th International conference on Bioinformatics and Bioengineering (BIBE)

作者： Delibasis, K. K. Plagianakos, V. P. Goudas, T. Maglogiannis, I. Univ Thessaly Dept Comp Sci & Biomed Informat Thessaloniki Greece Univ Piraeus Dept Digital Syst Piraeus Greece

ISBN: (纸本)9781479931637

In this work, we present a system, which uses computer vision techniques for human silhouette segmentation from video in indoor environments and a parametric 3D human model, in order to recognize the posture of the monitored person. the video data are acquired indoors from a fixed fish-eye camera in the living environment. the implemented 3D human model collaborates with a fish-eye camera model, allowing the calculation of the real human position in the 3D-space and consequently recognizing the posture of the monitored person. the paper discusses briefly the details of the human segmentation, the camera modeling and the posture recognition methodology. Initial results are also presented for a small number of video sequences.

关键词： assisted living image segmentation image sensors image sequences patient monitoring pose estimation solid modelling video signal processing

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