| Title |
Investigation of Simulation and Measuring Algorithm of Partial Discharge for Diagnosis of Electric Machinery Deterioration |
| Authors |
Hyeong-Taek Jang ; Sun-Geun Kwack ; Pan-Seok Shin ; Chang-Eob Kim ; Gyo-Bum Chung |
| DOI |
http://dx.doi.org/10.5207/JIEIE.2011.25.8.030 |
| Keywords |
Electric Machinery ; Mold Transformer ; Partial Discharge ; Artificial-Intelligent Diagnosis Method ; Neural Network |
| Abstract |
This paper proposes a new intelligent diagnosis equipment for the partial discharge, which keeps deteriorating the insulating materials inside electric machineries, ultimately leading to electrical breakdown. In order to simulate experimentally the partial discharge inside the electric machinery, the tip-to-plate, the sphere-to-plate, the sphere-to-sphere and the plate-to-plate electrodes are used respectively, of which the gaps are 1[㎜], 3[㎜] or 5[㎜] and the applied voltages are 3[㎸], 5[㎸] or 7[㎸]. Ceramic coupler sensor and FIR digital filter are used to measure the partial discharge and the artificial neural network is used for the deterioration diagnosis of the electric machinery. The microprocessor of PD diagnosis equipment is DSP (TMS320C6713) with FPGA (CycloneⅡ). The results of the real-time and on-line experiments performed with the developed equipment are also explained. |