Study On Partial Discharge On-line Detection Technology Of Electric Cable

Power cable has become an important part of urban power grid,so its insulation state is of great significance to the safe and reliable operation of power grids.After many years of operation,part of the cable has entered the fault period,which is due to factors such as aging.Partial Discharge detection technology,can help to find the problems in time,which is aimed at ensuring for the safe and reliable operation of the power grid.The effectiveness of application of detection technology in the field,however,remains to be improving.In view of the existing interference problem during online detection of power cable,we put forward program-controlled frequency selective hardware improvement method,and the anti-interference algorithm of clustering according to frequency in this paper.Through simulation analysis characteristics of the signal frequency change law in the cable transmission,we verify the feasibility of the proposed algorithm.Through simulation of the effect of filter by LabVIEW software,we determine selection scheme of the amplifier filtering parameter.By simulation of signal propagation by Simulink software,we conclude that signals of different frequency components make different propagation characteristics,and that as the frequency higher,and the attenuation stronger,the signal delay will be more serious.The factors above will cause the final synthesis of signal distortion.By the above analysis,we can conclude that,if we assume there are several discharge sources on the field detection,which have different discharge types,or discharge position,we are sure that the signals which are collected by the sensor will be different on frequency components.Developed on the basic of the theoretical simulation,we develop a programmable frequency selective amplifier,and form a complete set of hardware system which have a corresponding clustering algorithm base on the frequency information,and an automatic separation algorithm.Then we use the LabVIEW software to write a set of test procedures.To test the separation effect of the automatic clustering software,we carry on the systematic contrast test.After the test,we verify that,for different data sets,the software system can be optimized,appropriate separation clustering algorithm,and realize the intelligent automatic classification of data set.Finally,we establish the platform test,to verify the effects of this system while there are several discharge sources coexisting.The specific way is to arrange three discharge sources in the high voltage test hall and make the three sources coincidence discharge,at the same time we test the system for the separation of multi-source discharge capacity.What can be verified by test is that,the detection system is effective for the separation of sources under the complicated working condition of the coexistence of multiple source discharge,so that it can take correct diagnosis.