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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/102464

    Title: 類神經系統應用導電混凝土改善高壓輸電塔擊接地之配比最佳化
    Other Titles: Optimal design of conductive concrete to improve the anti-lightning grounding of electricitytransmission tower by using artificial neural networks
    Authors: 劉權毅;Liu, Chuan-I
    Contributors: 淡江大學土木工程學系碩士班
    Keywords: 雷擊;類神經網路;高導電混凝土;Lightning strikes;artificial neural networks;highly conductive concrete
    Date: 2014
    Issue Date: 2015-05-04 09:56:31 (UTC+8)
    Abstract: 造成輸電系統跳電故障的原因很多,由於台灣地區雷擊密度相當高,根據台灣電力公司統計,輸電系統由雷擊原因造成的機電事故已接近全部事故的50%,在整體上佔有相當的嚴重性。
    Due to high domestic lightning density, there are many reasons to cause electricity transmission system failure. According to Taipower (Taiwan Power Company, TPC, also known as Taipower) statistics, in the transmission system, the electrical accident came from lightning strikes were close to 50% of all accidents.
    In recent years, due to insufficient of grounding web, domestic equipment damage happened continuously. Lightning strikes are major natural disaster. Therefore, good grounding device should be an important measure in lightning protection. In the lightning protection and grounding device, the smaller the grounding resistivity is, the lower the instantaneous voltage drops. Therefore, the risk of being struck by lightning becomes less with smaller grounding resistance value and reliable anti-lightning grounding equipment. This study proposes the use of highly conductive concrete basic structure to be a large area of grounding resistance with grounding grid and grounding rods sharing lightning current in parallel,then to drive the lightning strike current underground and reduce the power loss caused by power failure.
    Previous works on the main drag reduction methods including increasing the area of the grounding network, citing external grounding and using chemical reducing agent were likely to cause corrosion of the grounding conductor. The earth is a poor conductive object due to the high resistivity of the earth. Once the electric current flows into the earth, the resistance of earth would be close to zero because of its large cross-section.
    Artificial Neural Networks method is different from the traditional one which is a kind of parallel distributed processing computing model. The basic principle of operation is based on a large but simple processing unit, or called Neuron connected to each other; by using the whole processing unit by the simple arithmetic of the external input signal to process information, which is similar to many features and benefits of human brains.This study proposes the use of the Artificial Neural Networks training with cross-validation method and Train-and-Test method used in optimizing the cost,resistance, and compressive of highly conductive concrete.
    Appears in Collections:[土木工程學系暨研究所] 學位論文

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