Improved Bagging Algorithm for Pattern Recognition in UHF Signals of Partial Discharges

Abstract

This paper presents an Improved Bagging Algorithm (IBA) to recognize ultra-high-frequency (UHF) signals of partial discharges (PDs). This approach establishes the sample information entropy for each sample and the re-sampling process of the traditional Bagging algorithm is optimized. Four typical discharge models were designed in the laboratory to simulate the internal insulation faults of power transformers. The optimized third order Peano fractal antenna was applied to capture the PD UHF signals. Multi-scale fractal dimensions as well as energy parameters extracted from the decomposed signals by wavelet packet transform were used as the characteristic parameters for pattern recognition. In order to verify the effectiveness of the proposed algorithm, the back propagation neural network (BPNN) and the support vector machine (SVM) based on the IBA were adopted in this paper to carry out the pattern recognition for PD UHF signals. Experimental results show that the proposed approach of IBA can effectively enhance the generalization capability and also improve the accuracy of the recognition for PD UHF signals.

Failure Prognosis of High Voltage Circuit Breakers with Temporal Latent Dirichlet Allocation

“…The existing literature covers a wide range of specific countermeasures, including mechanism dynamic features [8][9][10], dynamic contact resistance [11], partial discharge signal [12,13], decomposition gas [14], vibration [15], and spectroscopic monitoring [16]. Furthermore, numerous studies applied neural networks [8], support vector machine (SVM) [17], fuzzy logic [18], and other methods [19], to introduce more automation and intelligence into the signal analysis. However, these efforts were often limited to one specific aspect in their diagnosis of the failure conditions.…”

Classification of common partial discharge types in oil-paper insulation system using acoustic signals

“…Identifying sources of PD activities has been an important research area due to the PD's direct effect on insulation failure [10][11][12][13][14][15][16][17][18]. There are many attempts to achieve high recognition rate using AE signals for different PD types in the literature [1], [14][15][16][17][18].…”

“…For feature extraction, time-frequency transformation is proposed from the short time Fourier transform using seven descriptors as described in [13]. It shows different descriptors values based on averaging 11 training samples for each PD model.…”

Analysis of Time Domain Characteristic of Ultra-high Frequency Antenna Sensor Detecting Partial Discharge

“…This method is known as the UHF method in PD detection. Due to the high sensitivity and strong anti-interference capability, the UHF method has been widely employed in PD detection [1]. In field PD detection, the UHF method can effectively avoid the low-frequency electromagnetic interference and the corona discharge disturbance [2].…”