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Research And Development Of Anti-stealing Analysis System

Posted on:2018-03-12Degree:MasterType:Thesis
Country:ChinaCandidate:Q Q ShiFull Text:PDF
GTID:2348330515957474Subject:Engineering
Abstract/Summary:PDF Full Text Request
With the development of science and technology and the change of energy structure,the social development depends more and more on electric energy.The primary goal of the power industry is how to improve the energy structure and energy efficiency,how to meet the various needs of power applications and improve the security of power transmission economy and reliability.Under the influence of interest,some companies or individuals to take improper means to steal power,Which is reduce the efficiency of the use of electricity.How to better carryout anti-tampering work,especially for some unscrupulous businesses to monitor electricity is imminent.The traditional means of anti-stealing,such as the theft of the suspects user evidence is not only the timeliness of poor,low accuracy,on-site investigation of stealing behavior to obtain evidence and efficiency is not high.Development and promotion of anti-stealing analysis system has a very large practical significance.Based on the analysis of the common methods of stealing electricity and the corresponding anti-stealing methods,this paper summarizes the common means of stealing electricity,and designs the corresponding judging algorithm of stealing electricity.Based on the data collected by the power remote inspection device,10 kinds of abnormal alarm judgment algorithms are designed according to the common stealing methods.The anomaly of the alarm is mainly divided into two parts: the abnormal analysis of the system users and the hardware of the system supporting the remote inspection device anomaly analysis.Among them,the analysis of abnormal behavior of power consumption for users include: high frequency interference abnormal alarm,under voltage abnormal alarm,transformer over capacity abnormal alarm,wrong phase sequence abnormal alarm,tripping abnormal alarm and bottom jump alarm.An outlier algorithm based on Euclidean distance is applied to the anomaly decision process.Secondly,in order to better improve the efficiency of on-site investigation of stealing behavior to facilitate the prosecutors to evidence,the use of ionic development for mobile clients,ionic support existing mobile plat form such as ios and android,the system uses ionic to build applications of ios and android.
Keywords/Search Tags:anti-stealing, outlier algorithm, ionic, abnormal alar
PDF Full Text Request
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