Title | Research on a General Fast Analysis Algorithm Model for Pd Acoustic Detection System: The Software Development |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Huang, Xing-De, Fu, Chen-Zhao, Su, Lei, Zhao, Dan-Dan, Xiao, Rong, Lu, Qi-Yu, Si, Wen-Rong |
Conference Name | 2019 11th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) |
Date Published | apr |
Keywords | 2D PRPD histograms, 3G mobile communication, acoustic detection, Acoustic Fingerprints, acoustic signal detection, Automation, batch processing analysis, composability, data processing software, defect discharge data, developed software pages, easy fault location, fault diagnosis, fault location, gas insulated substations, general fast analysis algorithm model, GIS, Human Behavior, individual data file, insulation defect detection, intelligent analysis, Mechatronics, partial discharge measurement, pattern identification, PD acoustic detection system, PD AE signals analysis software, power engineering computing, power system equipments, pubcrawl, Q measurement, Resiliency, signal flow chart, Software development |
Abstract | At present, the AE method has the advantages of live measurement, online monitoring and easy fault location, so it is very suitable for insulation defect detection of power equipments such as GIS, etc. In this paper, development of a data processing software for PD acoustic detection based on a general fast analysis algorithm model is introduced. With considering the signal flow chart of current acoustic detection system widely used in operation and maintenance of power system equipments, the main function of the developed PD AE signals analysis software was designed, including the detailed analysis of individual data file, identification with phase compensation based on 2D PRPD histograms, batch processing analysis of data files, management of discharge fingerprint library and display of typical defect discharge data. And all of the corresponding developed software pages are displayed. |
DOI | 10.1109/ICMTMA.2019.00153 |
Citation Key | huang_research_2019 |