Research On Data Mining Of Traveling Wave Technology And Lightning Positioning System

According to related statistics show that lightning strike line trip is the main factor affecting security and stability of the line running.So,how to accurately determining whether the line is being struck by lightning and to judging the type of fault from the waveform,is conducive to the actual patrol line quickly locate and troubleshoot timely,improve power supply reliability.Application of traveling-wave technology and lightning location system provides a great help for fault recording and analysis.However,the measurement accuracy of the lightning location system affects by topography,and at the same time only big data of lightning strike information can not directly reflect the result of lightning strike line fault.Traveling-wave technology to identify in the first wave detection,it has accumulated more a lack of fault data.So,efficient collected and fully exploit the measured data in the failure information,can help us to improve the lightning location system functions,expand its scope of application;combined with the measured data targeted refining,expansion of the existing traveling wave algorithm.This paper will start with traveling wave fault identification,mining for LLS massive fault information extract the lightning location system on the relationship between lightning current amplitude and probe station efficiency,to make a attempt for lightning location system data mining.By traveling-wave technology the paper proposed a method to distinguish the fault information determining fault and non-fault and different fault types,and then in the lightning location system in the cluster analysis to obtain a more accurate the point of strike.On this basis,also conducted lightning current lightning detection and analysis of the correlation between a base station,and a line of Yunnan Honghe Prefecture conducted a lightning density statistics and trip rate calculation.