Abstract
This study developed an operating state diagnostic system based on partial discharge detection for analyzing faults in high-voltage motor stator windings. First, the partial discharge signal of the stator windings is measured with a high-frequency current sensor, and then phase-resolved partial discharge technology is used to convert it into three-dimensional graphics. A systematic analysis process involving the use of fractal theory architecture for fault extraction from the signal characteristics was designed for identifying faults and obtaining the fractal dimension and the lacunarity of the characteristic parameters. Similarity function defined extension theory was used for building a failure signature database for each fault. Finally, to design and build fuzzy membership function and inference systems for analyzing the operation status of the motor, the partial discharge energy value and fault type were used as indicators in fuzzy algorithms. The experimental results prove that the fuzzy diagnostic system proposed in this paper is combined with the important information of fault type and discharge quantity, where fault type is successfully recognized, and a more reliable high-voltage motor operating state monitoring technique is created. The findings are expected to monitor the operating state of high-voltage motor more effectively, thus, reducing additional maintenance costs resulted from heavy accidents.
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IEC: High-voltage test techniques—partial discharge measurements. IEC 60270 (2001)
Hudon, C., Bélec, M.: Partial discharge signal interpretation for generator diagnostics. IEEE Trans. Dielectr. Electr. Insul. 12(2), 297–319 (2005)
Satish, L., Zaengl, W.S.: Can fractal features be used for recognizing 3-D partial discharge patterns? IEEE Trans. Dielectr. Electr. Insul. 2(3), 352–359 (1995)
Gu, F.C., Chang, H.C.: Gas-insulated switchgear PD signal analysis based on Hilbert-Huang transform with fractal parameters enhancement. IEEE Trans. Dielectr. Electr. Insul. 20(4), 1049–1055 (2013)
Cai, W.: The extension set and incompatibility problem. J. Sci. Explor. 1(1), 81–93 (1983)
Cavallini, A., Montanari, G.C., Puletti, F., Contin, A.: A new methodology for the identification of PD in electrical apparatus: properties and applications. IEEE Trans. Dielectr. Electr. Insul. 12(2), 203–215 (2005)
Chao, K.H., Chen, P.Y.: An intelligent fault diagnosis method base on extension theory for DC-AC converters. Int. J. Fuzzy Syst. 17(1), 105–115 (2015)
IEC: Off-line partial discharge measurements on the stator winding insulation of rotating electrical machines. IEC 60034-27 (2006)
Zeng, B.Q.: Discussion on the issue using the generator coil of the PD source detection. Taiwan Power Company Eng. J. 2, 27–40 (2010)
Renforth, L.A., Hamer, P.S., Clark, D.: High-voltage rotating machines: a new technique for remote partial discharge monitoring of the stator insulation condition. IEEE Ind. Appl. 20(6), 79–89 (2014)
Chang, J.H., Lee, H.H.: A study on reliability based assessment algorithm for high voltage induction stator windings. In: Proceedings of the IPMHVC Conference, pp. 600–603 (2012)
Ueta, G., Wada, J., Okabe, S., Miyashita, M., Nishida, C., Kamei, M.: Insulation characteristics of epoxy insulator with internal delamination-shaped micro-defects. IEEE Trans. Dielectr. Electr. Insul. 20(5), 1851–1858 (2013)
Ueta, G., Wada, J., Okabe, S., Miyashita, M., Nishida, C., Kamei, M.: Insulation characteristics of epoxy insulator with internal void-shaped micro-defects. IEEE Trans. Dielectr. Electr. Insul. 20(2), 535–543 (2013)
Liese, M., Brown, M.: Design-dependent slot discharge and vibration sparking on high voltage windings. IEEE Trans. Dielectr. Electr. Insul. 15(4), 927–932 (2008)
Song, J., Li, C., Lin, L., Lei, Z., Bi, X.Y.: Slot discharge pattern of 10 kV induction motor stator coils under condition of insulation degradation. IEEE Trans. Dielectr. Electr. Insul. 20(6), 2091–2098 (2013)
Strachan, S.M., Rudd, S., Judd, M.D.: Knowledge-based diagnosis of partial discharges in power transformers. IEEE Trans. Dielectr. Electr. Insul. 15(1), 259–268 (2008)
Sureshjani, S.A., Kayal, M.: A novel technique for online partial discharge pattern recognition in large electrical motors. In: Proceedings of the ISIE Conference, pp. 721–726 (2014)
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The research was supported by the Ministry of Science and Technology of the Republic of China, under Grant No. MOST 103-2221-E-011-077-MY2.
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Chang, HC., Lin, SC., Kuo, CC. et al. Fuzzy Theory-Based Partial Discharge Technique for Operating State Diagnosis of High-Voltage Motor. Int. J. Fuzzy Syst. 18, 1092–1103 (2016). https://doi.org/10.1007/s40815-016-0210-0
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DOI: https://doi.org/10.1007/s40815-016-0210-0