局部放电脉冲电流波形宽带检测技术研究

bǃmono-exponential attenuation oscillation pulse
Abstract--Feature extraction methods for time-frequency energy distribution (TFED) using moment, marginal and Renyi information are studied in this paper. They are developed by combination of TFED’s own characteristics with mathematic statistic and information entropy. The Wigner-Ville Distribution (WVD) of a simulated PD pulse is chosen as the subject investigated to illustrate those methods, which gives the result of time and frequency moments, time and frequency marginals and Renyi information for the TFED. The results show that those methods can exactly and easily make feature extraction for the TFED of PD pulse, which can be used to PD pattern recognition and in-depth study of PD mechanism in the electrical insulation system. Index Terms-- PD pulse, time-frequency energy distribution, feature extraction, moment and marginal, Renyi information.
Fig. 2. Time moment of the PD pulse’s WVD. (a) the first order, (b) the second order.
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2008 International Conference on Condition Monitoring and Diagnosis, Beijing, China, April 21-24, 2008
Feature Extraction Methods for Time Frequency Energy Distribution of PD Pulse
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(11)
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t TFD(t , f )dt TFD(t , f )dt
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Fig. 3. Frequency moment of the PD pulse’s WVD. (a) the first order, (b) the second order.
WVDx (t , f )
x (t ) x* (t )e j 2S f W dW (5) 2 2 This distribution satisfies a large number of desirable mathematical properties, as summarized in the reference [6], P ( x) Ae t / W (1) [8] and [10]. In this paper, the author uses the WVD to 1 process the PD pulse shape as a representative example of the This work was supported by the High Voltage Division, School of TFED and do some study on the feature extraction methods
III. TIME AND FREQNECY MOMENT From the basic mathematical statistics, if the singlevariable X and the probability density function f ( x) are given, the kth order moment Pk is defined as
Wenrong Si, Junhao Li, Peng Yuan and Yanming Li
School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China *E-mail : siwenrong@
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Fig. 1. PD pulse shape and its WVD. (a) PD pulse shape, (b) WVD.
From now on, there are so many time-frequency analysis methods developed to process the non-stationary signals. A TFED which is particularly interesting is the Wigner-Ville Distribution (WVD) defined as
I. INTRODUCTION he partial discharge (PD) would not lead to instantaneous breakdown, but it is always the ultimate cause to insulation deterioration and eventually breakdown. Therefore, PD detection becomes the most popular method to evaluate dielectric insulation. A lot of investigation and experiment had done on the UWB detection technique for the PD pulse and many signal processing methods for PD pulse shape had been used, such as FFT, Wavelet Analysis, Time-frequency Analysis, and so on, all of which make a good help to PD pattern recognition and in-depth study of PD mechanism in the electrical insulation system. According to the non-stationary of PD pulse signals, the joint time-frequency is put forward to process the PD pulse shape to obtain its characteristics in time-frequency domain in this paper. And focus is made on the feature extraction methods for Time-frequency Energy Distribution (TFED) of PD pulse shape. II. PD PLUSE AND TIME-FREQUENCY ENERGY DISTRIBUTION The theoretical and practical conditions show that there is a damped oscillation of the PD pulse when it transmits from the PD original source to the detection points. This makes a big difference of the PD pulse shape detected with a UWB sensor from the real one. So the PD pulse shape can be defined as aǃmono-exponential pulse
A(e t / W e t / W ) sin 2S f c t
(4)
W and f c are the amplitude, the damped factor and
the oscillation frequency of the PD pulse shape, respectively. A simulated PD pulse shape is shown in the figure 1(a) with the expression (2), where the f c 100 MHz.
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Electrical Engineering, Xi’an Jiaotong University.
978-1-4244-1622-6/08/$25.00 ©2007 IEEE
for the WVD which are also fit for other TFEDs [6]. The WVD of the simulated PD pulse is shown in the figure 1(b).