Study On The Catenary Insulators’ Online Monitoring

As the rapid promotion of the national railway, all kinds of insulators have been widely applied in electrified railway. At the same time, owing to special environment, it’s normal for catenary insulators being polluted seriously than other power line insulators. Specially, with the "four vertical and four horizontal" Passenger Dedicated Line and other inter-provincial, inter-regional long-distance high-speed railway have been put into operation, catenary insulation need higher requirements because the affecting factors(environment, climate, distribution of companies etc.) are becoming more complex. The hazy weather has been persistent in most regions of China recently, adding to the contamination degree of catenary insulators. It’s not only likely to cause catenary insulator discharge phenomenon, but also flashover and severe line trip. That brings the normal operation of the traction power supply system great security risk. Therefore, it is necessary to carry out the on-line monitoring of catenary insulators, analyzing of surface contamination situation, identifying flashover potential risks, taking timely measures to prevent sudden failure, both to avoid catastrophic equipment failure, also avoid disrepair or overabundance, providing technical support for promoting the sustainable development of the railway. It has some practical significance.In this paper, in order to achieve the purpose of catenary insulators’ on-line monitoring, summarizing the characteristics of domestic operating state of contaminated insulators. Based on surface discharge theory, in view of leakage current flowing through the insulators’ surface contamination, an on-line monitoring scheme of catenary insulators’contamination is proposed and key issues are analyzed. Recur to the artificial pollution testing by the test platform in XIHARI, leakage current data is collected under different environmental and different contamination levels.As to mathematical expression of leakage current signal, the time domain and frequency domain analysis are used to extract the characteristic parameters of the leakage current signal. On the one hand, three time domain characteristics, i.e., root mean square of leakage current, maximum value and the standard deviation, are extracted. The relationships between these three parameters and environmental parameters, the degree of contamination are analyzed.On the other, as one of the frequency domain characteristics, the ratio of amplitude value between3th harmonic component and the fundamental,5th harmonic component and the3rd are extracted from the FFT transformation. The ratio of amplitude value between5th harmonic component and the3rd is adopted as the frequency domain characteristics. Secondly, as a time-frequency signal analysis tool, Short Time Fourier Transform (STFT) was employed to analyze the details of the time-frequency distribution. The correlation between the form factor of power spectral (the other frequency domain characteristics) and the degree of the contamination is established. Research shows that these five parameters of leakage current could provide useful information to predict contamination degree.Finally, in order to increase the applicability of the model, taking into account the impact of different creepage distance, the time domain characteristics extracted are corrected. Combining with the frequency domain characteristic parameter, in view of the environmental impact of the relative humidity, a contamination prediction model based on BP neural network is established and verified. Tests showed that the model can provide some data reference and guidance for dirty cleaning and anti pollution flashover.