Novel trend of "l" shape in PD pattern to judge the appropriate crucial moment of replacing cast-resin current transformer

This paper aims to address the problem of equipment fault prevention by preventive diagnosis of its insulation. Preventive diagnosis, as the name implies, means the accurate judgment made in advance on when power equipment can be replaced from on-site service before its breakdown. The experimentation, via voltage-stress aging tests and partial-discharge (PD) measurements, investigates the degree to which the insulation for cast-resin current transformers deteriorates. Five cast-resin current transformers of various insulation statuses are used for measurement in the laboratory. The measured discharge amounts are rearranged into parameters such as the average discharge amount and the discharge zone, and the relationships between the development trends of these two parameters' and the speed at which the insulation deterioration evolutional tracks are discussed in this study. This paper, aimed at equipment fault prevention by pre-diagnosis of the insulation used, applies high-voltage aging tests and PD measurements to investigate the speed of insulation deterioration evolutional track for cast-resin current transformers. This investigation discovers that the way in which the insulation deterioration evolutional tracks can be divided into three stages. With the wavelet transformation, we can clearly demonstrate the speed of insulation deterioration evolutional track via an insulation-aging characteristic diagram, which comprises the average discharge amounts and the discharge zones, to find out the reference criteria for imminent faults or failures. Finally, the "lscr " shape is proposed which is very helpful for the pre-diagnosis of cast-resin current transformers.

[1]  L. Niemeyer,et al.  Measurement and simulation of PD in epoxy voids , 1995 .

[2]  Hengkun Xie,et al.  A new technique for extracting partial discharge signals in on-line monitoring with wavelet analysis , 1998, Proceedings of 1998 International Symposium on Electrical Insulating Materials. 1998 Asian International Conference on Dielectrics and Electrical Insulation. 30th Symposium on Electrical Insulating Ma.

[4]  Xiandong Ma,et al.  Automated wavelet selection and thresholding for PD detection , 2002 .

[5]  Xiandong Ma,et al.  Interpretation of wavelet analysis and its application in partial discharge detection , 2002 .

[6]  P. von Glahn,et al.  Continuous recording and stochastic analysis of PD , 1995 .

[7]  Robert M. Hamer,et al.  Data Analysis for Research Designs: Analysis of Variance and Multiple Regression/Correlation Approaches , 1990 .

[8]  R. Vogelsang,et al.  Detection of electrical tree propagation by partial discharge measurements , 2005 .

[9]  Ajit S. Bopardikar,et al.  Wavelet transforms - introduction to theory and applications , 1998 .

[10]  F. H. Kreuger,et al.  Partial Discharge Detection in High Voltage Equipment , 1990 .

[11]  P.H.F. Morshuis,et al.  Partial discharge mechanisms in voids related to dielectric degradation , 1995 .

[12]  Hong Li,et al.  Theory and application of dynamic aging for life estimation in machine insulation , 2000 .

[13]  E. Gulski,et al.  Classification of partial discharges , 1993 .

[14]  Ruay‐Nan Wu,et al.  Insulation status assessment of cast‐resin current transformers based on digital partial discharge measurement , 2007 .

[15]  Michael G. Danikas Assessment of Deterioration in Epoxy/Mica Machine Insulation , 1993 .

[16]  E. Gulski,et al.  Influence of aging on classification of PD in HV components , 1995 .