937 research outputs found

    Sensor Network Architectures for Monitoring Underwater Pipelines

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    This paper develops and compares different sensor network architecture designs that can be used for monitoring underwater pipeline infrastructures. These architectures are underwater wired sensor networks, underwater acoustic wireless sensor networks, RF (Radio Frequency) wireless sensor networks, integrated wired/acoustic wireless sensor networks, and integrated wired/RF wireless sensor networks. The paper also discusses the reliability challenges and enhancement approaches for these network architectures. The reliability evaluation, characteristics, advantages, and disadvantages among these architectures are discussed and compared. Three reliability factors are used for the discussion and comparison: the network connectivity, the continuity of power supply for the network, and the physical network security. In addition, the paper also develops and evaluates a hierarchical sensor network framework for underwater pipeline monitoring

    Performance enhancement of sensor network architecture for monitoring underwater oil pipeline

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    In this paper, a deployment mechanism is designed to distribute heterogeneous nodes to optimally cover the pipeline where the mechanism helps locate each node on the wall of the oil pipeline where the number of nodes can be increased depending on this mechanism. The six-layer network hierarchy includes basic sensor nodes (BSN), aggregation relay node (ARN) that added to the network hierarchy, data relay nodes (DRN), data dissemination node (DDN), base station (sinks), and network control center (NCC). This network relies on the improved smart redirect or jump algorithm (SRJ) by sending packets depend on the active relay nodes in both directions that are within the transmission range of the ARNs instead of relying on the number of hops adopted by the SRJ algorithm to reduce the network delay, the energy consumed in relay nodes, and the number of times the DRNs increased transmission range. The OMNeT++ and MATLAB programs were used to implement the simulation scenario. The results showed superiority in terms of the average overhead communication, energy consumption, and end to the end delay with network delay in some cases rely on the number of active relay nodes

    Magnetic Flux Leakage techniques for detecting corrosion of pipes

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    Oil and gas pipelines are subjected to corrosion due to harsh environmental conditions as in refinery and thermal power plants. Interesting problems such as internal and external corrosion, emerging from the increasing demand for pipeline protection have prompted this study. Thus, early detection of faults in pipes is essential to avoid disastrous outcomes. The research work presented in this thesis comprises investigations into the use of magnetic flux leakage (MFL) testing for pipe in extreme (underwater and high temperature) conditions. The design of a coil sensor (ferrite core with coil) with a magnetic circuit is carried out for high temperature conditions. The sensor thus developed lays the ground for non-destructive evaluation (NDE) of flaws in pipes through the MFL technique. The research focusses on the detection and characterization of MFL distribution caused by the loss of metal in ferromagnetic steel pipes. Experimental verifications are initially conducted with deeply rusted pipe samples of varying thicknesses in air. AlNiCo magnets are used along with Giant Magneto Resistance (GMR) sensor (AA002-02). The experiment is further repeated for saltwater conditions in relation to varying electrical conductivity with radio frequency identification (RFID) technique. A further study carried out in the research is the correlation between magnetic and underwater data communication. The study has resulted in the development and experimental evaluation of a coil sensor with its magnetic response at room and high temperatures. This makes the system effective under high temperature conditions where corrosion metal loss needs to be determined

    Magnetic Flux Leakage techniques for detecting corrosion of pipes

    Get PDF
    Oil and gas pipelines are subjected to corrosion due to harsh environmental conditions as in refinery and thermal power plants. Interesting problems such as internal and external corrosion, emerging from the increasing demand for pipeline protection have prompted this study. Thus, early detection of faults in pipes is essential to avoid disastrous outcomes. The research work presented in this thesis comprises investigations into the use of magnetic flux leakage (MFL) testing for pipe in extreme (underwater and high temperature) conditions. The design of a coil sensor (ferrite core with coil) with a magnetic circuit is carried out for high temperature conditions. The sensor thus developed lays the ground for non-destructive evaluation (NDE) of flaws in pipes through the MFL technique. The research focusses on the detection and characterization of MFL distribution caused by the loss of metal in ferromagnetic steel pipes. Experimental verifications are initially conducted with deeply rusted pipe samples of varying thicknesses in air. AlNiCo magnets are used along with Giant Magneto Resistance (GMR) sensor (AA002-02). The experiment is further repeated for saltwater conditions in relation to varying electrical conductivity with radio frequency identification (RFID) technique. A further study carried out in the research is the correlation between magnetic and underwater data communication. The study has resulted in the development and experimental evaluation of a coil sensor with its magnetic response at room and high temperatures. This makes the system effective under high temperature conditions where corrosion metal loss needs to be determined

    Multimodal, software defined networking for subsea sensing and monitoring.

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    The prevalence of oceanic industry and ocean borne interests has given rise to the concept of the Underwater Internet of Things as a vector for automation and data analytics in an environment hostile to anthropomorphic activity. Through the Internet of Underwater Things, it is theorised that sensors along the ocean floor or otherwise can be densely connected to the internet through wireless acoustic or optical links. However, both technologies have significant disadvantages that prevent either becoming a dominant technology. This project proposes a wireless software defined multimodal network infrastructure, that is proven using channel modelling and power analysis calculations, to be capable of robustly transmitting sensor data from source to sink by managing each technology according to its optimal environment. It was found that it is achievable to populate an opto-acoustic network in such a way that Successful Delivery Ratio becomes 90%-100% in clear water whilst achieving a 17% saving in overall energy consumption in a network mounted on a pipeline at 200 m depth when compared to a stand-alone equivalent acoustic network
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