12,032 research outputs found

    UHF diagnostic monitoring techniques for power transformers

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    This paper initially gives an introduction to ultra-high frequency (UHF) partial discharge monitoring techniques and their application to gas insulated substations. Recent advances in the technique, covering its application to power transformers, are then discussed and illustrated by means of four site trials. Mounting and installation of the UHF sensors is described and measurements of electrical discharges inside transformers are presented in a range of formats, demonstrating the potential of the UHF method. A procedure for locating sources of electrical discharge is described and demonstrated by means of a practical example where a source of sparking on a tap changer lead was located to within 15 cm. Progress with the development of a prototype on-line monitoring and diagnostic system is reviewed and possible approaches to its utilization are discussed. New concepts for enhancing the capabilities of the UHF technique are presented, including the possibility of monitoring the internal mechanical integrity of plant. The research presented provides sufficient evidence to justify the installation of robust UHF sensors on transformer tanks to facilitate their monitoring if and when required during the service lifetime

    Compressive Matched-Field Processing

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    Source localization by matched-field processing (MFP) generally involves solving a number of computationally intensive partial differential equations. This paper introduces a technique that mitigates this computational workload by "compressing" these computations. Drawing on key concepts from the recently developed field of compressed sensing, it shows how a low-dimensional proxy for the Green's function can be constructed by backpropagating a small set of random receiver vectors. Then, the source can be located by performing a number of "short" correlations between this proxy and the projection of the recorded acoustic data in the compressed space. Numerical experiments in a Pekeris ocean waveguide are presented which demonstrate that this compressed version of MFP is as effective as traditional MFP even when the compression is significant. The results are particularly promising in the broadband regime where using as few as two random backpropagations per frequency performs almost as well as the traditional broadband MFP, but with the added benefit of generic applicability. That is, the computationally intensive backpropagations may be computed offline independently from the received signals, and may be reused to locate any source within the search grid area

    A survey of localization in wireless sensor network

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    Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network

    Self-Positioning Smart Buoys, The \u27Un-Buoy\u27 Solution: Logistic Considerations Using Autonomous Surface Craft Technology and Improved Communications Infrastructure

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    Moored buoys have long served national interests, but incur high development, construction, installation, and maintenance costs. Buoys which drift off-location can pose hazards to mariners, and in coastal waters may cause environmental damage. Moreover, retrieval, repair and replacement of drifting buoys may be delayed when data would be most useful. Such gaps in coastal buoy data can pose a threat to national security by reducing maritime domain awareness. The concept of self-positioning buoys has been advanced to reduce installation cost by eliminating mooring hardware. We here describe technology for operation of reduced cost self-positioning buoys which can be used in coastal or oceanic waters. The ASC SCOUT model is based on a self-propelled, GPS-positioned, autonomous surface craft that can be pre-programmed, autonomous, or directed in real time. Each vessel can communicate wirelessly with deployment vessels and other similar buoys directly or via satellite. Engineering options for short or longer term power requirements are considered, in addition to future options for improved energy delivery systems. Methods of reducing buoy drift and position-maintaining energy requirements for self-locating buoys are also discussed, based on the potential of incorporating traditional maritime solutions to these problems. We here include discussion of the advanced Delay Tolerant Networking (DTN) communications draft protocol which offers improved wireless communication capabilities underwater, to adjacent vessels, and to satellites. DTN is particularly adapted for noisy or loss-prone environments, thus it improves reliability. In addition to existing buoy communication via commercial satellites, a growing network of small satellites known as PICOSATs can be readily adapted to provide low-cost communications nodes for buoys. Coordination with planned vessel Automated Identification Systems (AIS) and International Maritime Organization standards for buoy and vessel notificat- - ion systems are reviewed and the legal framework for deployment of autonomous surface vessels is considered

    CABE : a cloud-based acoustic beamforming emulator for FPGA-based sound source localization

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    Microphone arrays are gaining in popularity thanks to the availability of low-cost microphones. Applications including sonar, binaural hearing aid devices, acoustic indoor localization techniques and speech recognition are proposed by several research groups and companies. In most of the available implementations, the microphones utilized are assumed to offer an ideal response in a given frequency domain. Several toolboxes and software can be used to obtain a theoretical response of a microphone array with a given beamforming algorithm. However, a tool facilitating the design of a microphone array taking into account the non-ideal characteristics could not be found. Moreover, generating packages facilitating the implementation on Field Programmable Gate Arrays has, to our knowledge, not been carried out yet. Visualizing the responses in 2D and 3D also poses an engineering challenge. To alleviate these shortcomings, a scalable Cloud-based Acoustic Beamforming Emulator (CABE) is proposed. The non-ideal characteristics of microphones are considered during the computations and results are validated with acoustic data captured from microphones. It is also possible to generate hardware description language packages containing delay tables facilitating the implementation of Delay-and-Sum beamformers in embedded hardware. Truncation error analysis can also be carried out for fixed-point signal processing. The effects of disabling a given group of microphones within the microphone array can also be calculated. Results and packages can be visualized with a dedicated client application. Users can create and configure several parameters of an emulation, including sound source placement, the shape of the microphone array and the required signal processing flow. Depending on the user configuration, 2D and 3D graphs showing the beamforming results, waterfall diagrams and performance metrics can be generated by the client application. The emulations are also validated with captured data from existing microphone arrays.</jats:p

    Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm

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    Offshore Wind has become the most profitable renewable energy source due to the remarkable development it has experienced in Europe over the last decade. In this paper, a review of Structural Health Monitoring Systems (SHMS) for offshore wind turbines (OWT) has been carried out considering the topic as a Statistical Pattern Recognition problem. Therefore, each one of the stages of this paradigm has been reviewed focusing on OWT application. These stages are: Operational Evaluation; Data Acquisition, Normalization and Cleansing; Feature Extraction and Information Condensation; and Statistical Model Development. It is expected that optimizing each stage, SHMS can contribute to the development of efficient Condition-Based Maintenance Strategies. Optimizing this strategy will help reduce labor costs of OWTs׳ inspection, avoid unnecessary maintenance, identify design weaknesses before failure, improve the availability of power production while preventing wind turbines׳ overloading, therefore, maximizing the investments׳ return. In the forthcoming years, a growing interest in SHM technologies for OWT is expected, enhancing the potential of offshore wind farm deployments further offshore. Increasing efficiency in operational management will contribute towards achieving UK׳s 2020 and 2050 targets, through ultimately reducing the Levelised Cost of Energy (LCOE)

    Sensor-assisted Video Mapping of the Seafloor

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    In recent years video surveys have become an increasingly important ground-truthing of acousticseafloor characterization and benthic habitat mapping studies. However, the ground-truthing and detailed characterization provided by video are still typically done using sparse sample imagery supplemented by physical samples. Combining single video frames in a seamless mosaic can provide a tool by which imagery has significant areal coverage, while at the same time showing small fauna and biological features at mm resolution. The generation of such a mosaic is a challenging task due to height variations of the imaged terrain and decimeter scale knowledge of camera position. This paper discusses the current role of underwater video survey, and the potential for generating consistent, quantitative image maps using video data, accompanied by data that can be measured by auxiliary sensors with sufficient accuracy, such as camera tilt and heading, and their use in automated mosaicking techniques. The camera attitude data also provide the necessary information to support the development of a video collage. The collage provides a quick look at the large spatial scale features in a scene and can be used to pinpoint regions that are likely to yield useful information when rendered into high-resolution mosaics. It is proposed that high quality mosaics can be produced using consumer-grade cameras and low-cost sensors, thereby allowing for the economical scientific video surveys. A case study is presented with the results from benthic habitat mapping and the ground-truthing ofseafloor acoustic data using both real underwater imagery and simulations. A computer modeling of the process of video data acquisition (in particular on a non-flat terrain) allows for a better understanding of the main sources of error in mosaic generation and for the choice of near-optimal processing strategies. Various spatial patterns of video survey coverage are compared and it is shown that some patterns have certain advantages in the sense of accumulated error and overall mosaic accuracy

    Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices

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    Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments; where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution, tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally, we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance
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