7,993 research outputs found

    Self-Calibration Methods for Uncontrolled Environments in Sensor Networks: A Reference Survey

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    Growing progress in sensor technology has constantly expanded the number and range of low-cost, small, and portable sensors on the market, increasing the number and type of physical phenomena that can be measured with wirelessly connected sensors. Large-scale deployments of wireless sensor networks (WSN) involving hundreds or thousands of devices and limited budgets often constrain the choice of sensing hardware, which generally has reduced accuracy, precision, and reliability. Therefore, it is challenging to achieve good data quality and maintain error-free measurements during the whole system lifetime. Self-calibration or recalibration in ad hoc sensor networks to preserve data quality is essential, yet challenging, for several reasons, such as the existence of random noise and the absence of suitable general models. Calibration performed in the field, without accurate and controlled instrumentation, is said to be in an uncontrolled environment. This paper provides current and fundamental self-calibration approaches and models for wireless sensor networks in uncontrolled environments

    A Sparsity-Based Method for Blind Compensation of a Memoryless Nonlinear Distortion: Application to Ion-Selective Electrodes

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    International audience— In this paper, we propose a method for blind compensation of a memoryless nonlinear distortion. We assume as prior information that the desired signal admits a sparse representation in a transformed domain that should be known in advance. Then, given that a nonlinear distortion tends to generate signals that are less sparse than the desired one, our proposal is to build a compensating function model that gives rise to a maximally sparse signal. The implementation of this proposal has, as central elements, a criterion built upon an approximation of the 0-norm, the use of polynomial functions as compensating structures, and an optimization strategy based on sequential quadratic programming. We provide a theoretic analysis for an 0-norm criterion and results considering synthetic data. We also employ the method in an actual application related to chemical analysis via ion-selective electrode arrays

    Frequency-sweep examination for wave mode identification in multimodal ultrasonic guided wave signal

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    This article has been made available through the Brunel Open Access Publishing Fund.Ultrasonic guided waves can be used to assess and monitor long elements of a structure from a single position. The greatest challenges for any guided wave system are the plethora of wave modes arising from the geometry of the structural element which propagate with a range of frequency-dependent velocities and the interpretation of these combined signals reflected by discontinuities in the structural element. In this paper, a novel signal processing technique is presented using a combination of frequency-sweep measurement, sampling rate conversion, and Fourier transform. The technique is applied to synthesized and experimental data to identify different modes in complex ultrasonic guided wave signals. It is demonstrated throughout the paper that the technique also has the capability to derive the time of flight and group velocity dispersion curve of different wave modes in field inspections. © 2014 IEEE

    Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

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    The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

    Nonlinear time-warping made simple: a step-by-step tutorial on underwater acoustic modal separation with a single hydrophone

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    © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Bonnel, J., Thode, A., Wright, D., & Chapman, R. Nonlinear time-warping made simple: a step-by-step tutorial on underwater acoustic modal separation with a single hydrophone. The Journal of the Acoustical Society of America, 147(3), (2020): 1897, doi:10.1121/10.0000937.Classical ocean acoustic experiments involve the use of synchronized arrays of sensors. However, the need to cover large areas and/or the use of small robotic platforms has evoked interest in single-hydrophone processing methods for localizing a source or characterizing the propagation environment. One such processing method is “warping,” a non-linear, physics-based signal processing tool dedicated to decomposing multipath features of low-frequency transient signals (frequency f  1 km). Since its introduction to the underwater acoustics community in 2010, warping has been adopted in the ocean acoustics literature, mostly as a pre-processing method for single receiver geoacoustic inversion. Warping also has potential applications in other specialties, including bioacoustics; however, the technique can be daunting to many potential users unfamiliar with its intricacies. Consequently, this tutorial article covers basic warping theory, presents simulation examples, and provides practical experimental strategies. Accompanying supplementary material provides matlab code and simulated and experimental datasets for easy implementation of warping on both impulsive and frequency-modulated signals from both biotic and man-made sources. This combined material should provide interested readers with user-friendly resources for implementing warping methods into their own research.This work was supported by the Office of Naval Research (Task Force Ocean, project N00014-19-1-2627) and by the North Pacific Research Board (project 1810). Original warping developments were supported by the French Delegation Generale de l'Armement

    System optimization of an all-silicon IQ modulator : achieving 100 Gbaud dual polarization 32QAM

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    We experimentally demonstrate the highest, to the best of our knowledge, reported net rate in a SiP IQ modulator. At 100 Gbaud 32QAM (quadrature amplitude modulation), and assuming 20% FEC (forward error correction) overhead, we achieved a dual polarization net rate of 833 Gb/s. This record was achieved by adapting digital signal processing to the challenging pattern dependent distortion encountered in the nonlinear and bandwidth limited regime. First the Mach Zehnder modulator (MZM) operating point (trading off modulation efficiency and 3 dB bandwidth) and linear compensation (electrical and optical) are jointly optimized. Next, the key application of nonlinear preand post-compensation are explored. We show that nonlinear processing at the transmitter, in our case an iterative learning control (ILC) method, is essential as post-processing alone could not achieve reliable communications at 100 Gbaud. Nonlinear post-compensation algorithms pushed the performance under the FEC threshold with the introduction of structured intersymbol interference in post processing and a simple one-step maximum likelihood sequence detector. We provide detailed descriptions of our methodology and results
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