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Acoustic data communication system for in-pipe wireless sensor networks

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dc.contributor.advisor Eduardo Kausel. en_US
dc.contributor.author Kokossalakis, George, 1976- en_US
dc.contributor.other Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering. en_US
dc.date.accessioned 2007-10-22T16:21:35Z
dc.date.available 2007-10-22T16:21:35Z
dc.date.copyright 2006 en_US
dc.date.issued 2006 en_US
dc.identifier.uri http://dspace.mit.edu/handle/1721.1/34379 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/34379
dc.description Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2006. en_US
dc.description Includes bibliographical references. en_US
dc.description.abstract Sustainability of aging infrastructure is one of the greatest current civil engineering challenges, especially in the case of pipelines, where no direct access is available. Being simultaneously massive and distributed, their normal operation is critical for the health and prosperity of the community. In current practice, the condition of pipelines is assessed by non-destructive inspection techniques. Nonetheless, frequent pipeline failures warrant the continuous assessment of their condition, in order to schedule the maintenance activities accordingly, and assure their safe operation. Continuous monitoring necessitates the deployment of autonomous wireless sensor networks (WSN). This thesis proposes solutions for the communication and power units of a WSN for monitoring underground water pipelines. Regarding the communication unit, it is proposed to use the pipeline as an acoustic waveguide for the transmission of appropriately modulated acoustic waves that encapsulate the digital data, since radio frequency transmission is not feasible underground. The confined acoustic channel imposes severe distortion on the propagating signal. In order to compensate for the dispersion and ambient noise, the proposed communication system employs an elaborate set of signal processing steps, such as Reed-Solomon Encoding, Barker Code Synchronization, Adaptive Equalization, Bandpass Filtering, Stacking and application of Inverse Transfer Function techniques. The robust performance of the proposed system is evaluated and verified by means of numerical simulations and scaled laboratory experiments. en_US
dc.description.abstract (cont.) The bandwidth vs. power relationship is identified as the major trade-off for its design, since the in-pipe acoustic channel is bandwidth limited, while the WSN application is power limited. Excessive bandwidth use would impose severe distortion on the propagating signal, while power limitations restrict the use of bandwidth efficient digital communication techniques. In order to address the power availability, a miniature power harvesting system, extracting energy from the flow of water inside the pipeline, is proposed, composed of a generator and a turbine combination. A hybrid design presenting the high efficiency of Gorlov's helical turbine and the high startup torque of Savonius turbine is provided. The resulting power harvesting system is capable of sustaining a continuous 1 watt of power under normal water pipeline operating conditions. en_US
dc.description.statementofresponsibility by George Kokossalakis. en_US
dc.format.extent 294 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/34379 en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582
dc.subject Civil and Environmental Engineering. en_US
dc.title Acoustic data communication system for in-pipe wireless sensor networks en_US
dc.type Thesis en_US
dc.description.degree Sc.D. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering. en_US
dc.identifier.oclc 70125314 en_US


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