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Analysis Of Typical Building Electrical Fire Fault And Its Pattern Recognition

Posted on:2017-06-14Degree:MasterType:Thesis
Country:ChinaCandidate:L JiaFull Text:PDF
GTID:2322330533950698Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
With the development of people's living standards and the national economy, usageenergy and needs is growing. In order to improve our ability to identify the electrical fire,international status and technical capability, it is necessary for us to improve identification technology as soon as possible to carry out electrical fire at a deeper level.First The paper main introduces a typical low-voltage distribution system, also studied the various components, electrical equipment and the protection of a series of devices, and so on are included. What's more, understand a series of typical electrical fault, which can cause fire. Through Analysis the basic principles of reason on a series of short-circuit,including leakage fault, the bad contact,overload, grounding, and so on, a series of consequences, slso,a precautionary measure is given.Through analyzing the typical construction of low-voltage distribution lines, we can establish its schematic. In this paper, a simulated model about low-voltage distribution system is established, semolina package of Matlabsets and line parameters, analyzes bad contact fault and a variety of short-circuit fault and so on, Matlab can simulate these process, waveform and presents the simulation results, the spread features of the faults are summed up.Last.based on analyzing the phenomenon of the equipment and lines, a feasible approach to making mathematical model to determine the possible location of the fault and the cause of the fire are proposed, on the use of artificial neural network, and after the occurrence of the fire. The result of tests and exercises displays this algorithm has many virtues, such as high accuracy and fast constringency, can provide identification technologies and reference for the electrical fire investigation.
Keywords/Search Tags:Electrical failure, Electrical fire, BP Neural Network, Matlab simulation
PDF Full Text Request
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