Partial Discharge Ultra-high Frequency Signals Research Articles

Simulation study of partial discharge UHF signal propagation characteristics in GIS

Insulation defects inside a Gas Insulated Switchgear (GIS) can generate partial discharges, and the current pulses caused by them can excite ultra-high frequency (UHF) electromagnetic waves. To study the attenuation characteristics of UHF signal propagation in GIS, simulation models of the straight cylinder, insulator, L-type, and T-type structures are established by CST simulation software. Then the propagation characteristics of partial discharge UHF signal are studied and analyzed. The simulation results show that the electromagnetic wave propagates in each structure inside the GIS with different degrees of attenuation. When passing through insulators continuously, the first insulator has the most serious attenuation; when passing through T-shaped structures, the attenuation of T-shaped vertical branches is more serious than linear branches.

A Fuzzy Interpolation Cross-Correlation Method for Time-Delay Estimation of Partial Discharge UHF Pulse Signals

Time-delay estimation of partial discharge (PD) ultrahigh-frequency (UHF) pulse signals is one of the effective means to diagnose the local defect of electrical equipment. In order to improve the time-delay estimation accuracy of a multielement PD UHF pulse signal sensor array and reduce the cost of the PD detection system, a fuzzy interpolation cross-correlation method for time-delay estimation of PD UHF pulse signals was proposed in this paper. Improving the signal sampling rate is an effective way to improve the time-delay estimation accuracy. In this work, the fuzzy interpolation inference method was applied to interpolate intermediate values into the feature area of the PD UHF signal to improve the sampling rate, and then the cross-correlation method was used to estimate the time delay. This method not only improves the system sampling rate by fuzzy interpolation inference, which can make up for the deficiency of system equipment sampling performance, but also reduces the estimation error caused by noninteger multiple sampling intervals of signal time delay. The comparative experiment results demonstrate the power of the proposed method in improving the accuracy of the time-delay estimation of PD UHF pulse signals.

Experimental Research on the Sensitivity of Partial Discharge Ultra High Frequency Sensor Structure Parameters

With the development of intelligent high voltage switch, online gas insulated switchgear discharge detection technology has been more and more widely applied. Because of the high sensing sensitivity and good antiinterference performance of build-in partial discharge sensor, it is currently required to install them on gas insulated switchgear products with voltage levels of 220 kV and above at the factory. The structural parameters of the build-in partial discharge sensor is of great importance to its sensing sensitivity. Therefore, in this paper, the influence of the structure change on the sensitivity of axisymmetric gas insulated switchgear build-in partial discharge sensor is experimentally studied. A practical gas insulated switchgear test model was established in the laboratory, and the frequency domain measurement system based on Spectrogram analyzer and synchronous sweep signal generator was adopted. By comparing the insertion loss generated by the build-in sensor when receiving sweep signal, the influence of structural parameter changes on the sensing sensitivity was analyzed. The results show that the diameter of the build-in sensor should be matched with the diameter of the hand-hole. The match of the larger diameter of the hand-hole and the smaller diameter of the sensor can increase the sensing sensitivity, but when the diameter of the sensor is close to the diameter of the hand-hole, the sensitivity will be significantly reduced. In addition, metal bolts with the sensor electrode and its insulating support fixed to the hand-hole cover can also result in a significant reduction in sensing sensitivity. Using the same measuring principle and system, the propagation attenuation characteristics of partial discharge ultra high frequency signal in gas insulated switchgear typical structures (linear and L-shaped structures) are also experimentally studied. The results show that the average attenuation of partial discharge ultra high frequency signal in gas insulated switchgear along the linear distance is 0.3 dB/m, and the attenuation through every L-shaped structure is 4.2 dB.

Partial Discharge Signal Extraction Method Based on EDSSV and Low Rank RBF Neural Network

The detection process of partial discharge (PD) ultra-high frequency (UHF) signal is easily affected by white noise and periodic narrowband noise, which hinder the fault diagnosis of high-voltage electrical appliances. In order to extract PD UHF signal and suppress noise effectively, this paper provides a new method to detect PD UHF signal by EDSSV and low rank RBF neural network. Firstly, the singular value decomposition (SVD) is performed on the mixed noises of PD signal. Secondly, the peak index of energy difference spectrum of singular value (EDSSV) is selected as optimal singular value threshold, and then the periodic narrowband noise is eliminated by reconstructing the effective rank order. Finally, radial basis function (RBF) neural network is used to approximate the denoised PD signal, and Gaussian window filter is used to extract the PD signal. To verify the performance of the proposed method, we compared it with other three algorithms in simulation and field detection, including adaptive singular value decomposition (ASVD), singular value decomposition based on S-transform and MTFM (S-SVD) and EMD-WT algorithms. Particularly, four evaluation indices are designed for the detection data, which consider both the noise suppression and feature preservation. The results demonstrate the validity of the proposed method with higher signal-to-noise ratio and less waveform distortion.

A Partial Discharge Detection Method for SF6 Insulated Inverted Current Transformers Adopting Inner Shield Case as UHF Sensor

A partial discharge (PD) detection method for SF6 insulated inverted current transformers (SIICTs) adopting an inner shield case as an ultra-high frequency (UHF) sensor is proposed in this paper. The inner shield case is a component of the SIICT. Its structure is similar to that of an antenna and can be used as a UHF sensor to measure the PD UHF signal. A 110 kV current transformer is used as an experimental object and the voltage standing-wave ratio of the inner shield case is calculated. The validity and sensitivity of this method are proved by experiments with ac voltage. This PD detection method solves the problem that the UHF sensor is difficult to mount inside current transformers and provides a novel method for PD detection of SIICTs.

Study on PD detection for GIS based on autocorrelation coefficient and similar Wavelet soft threshold

To address the issue of white noise at partial discharge (PD) ultra high frequency (UHF) signal in gas insulated substation (GIS), this paper develops an external sensor and proposes new empirical mode decomposition (EMD) denoising method based on autocorrelation coefficient and similar wavelet soft threshold. Four types of typical GIS defects at the PD UHF signal were obtained through experiment. The autocorrelation coefficient of intrinsic mode functions (IMF) components at the PD UHF signal was computed, the cut-off point between the noise signal dominant mode and the UHF signal dominant mode was found. The similar wavelet soft threshold denoising was performed on the signal which is dominated by the noise signal, all the UHF signals were finally reconstructed. The signal-to-noise ratio computed by the proposed denoising method was compared with the one computed by the wavelet denoising method, the results shows that the proposed denoising method in this paper is more effective than the wavelet denoising method.

On the Feasibility of Gap Detection of Power Transformer Partial Discharge UHF Signals: Gap Propagation Characteristics of Electromagnetic Waves

This study analyzed the transformer electromagnetic gap propagation characteristics. The influence of gap size is also analyzed, and the results experimentally verified. The obtained results indicated that the gap propagation characteristics of electromagnetic wave signals radiated by the partial discharge (PD) source in different directions are substantially different. The intensity of the electromagnetic wave in the gap reaches a maximum at a gap height of 1 cm; and inside the gap, the intensity of the electromagnetic wave depicted an increasing trend at the tail area of the gap. Finally, from the obtained results, some suggestions on where to install sensors in practical systems for ultra high frequency (UHF) PD signal detection in the transformer gap are provided. The obtained results confirmed the feasibility of using this approach. These results can be seen as a benchmark and a challenge for further research in this field.

Feature extraction of GIS partial discharge signal based on S‐transform and singular value decomposition

Partial discharge (PD) detection and recognition are of great significance to the condition monitoring of gas-insulated switchgear (GIS). In the current work, ultra-high-frequency (UHF) signals induced by PD current pulses are measured and used to represent PD source. For PD classification, feature parameters need to be extracted from UHF signals. Therefore, this study proposes a new feature extraction method that is based on S-transform (ST) and singular value decomposition (SVD). PD UHF signals generated by four kinds of artificial defects are collected and analysed. ST is used to acquire the joint time–frequency information of the PD UHF signal. SVD is used to acquire the time–frequency characteristics of the UHF signal. Based on the distribution difference of time–frequency characteristics of different kinds of PDs, a 24-demensional feature vector is finally extracted. Support vector machine optimised by particle swarm optimisation algorithm is employed as classifier to recognise the four kinds of PDs. Results show that the proposed feature extraction method can effectively identify the designed four kinds of PDs even with few samples and strong background noise.

Antipodal Vivaldi Antenna to Detect UHF Signals That Leaked Out of the Joint of a Transformer

In recent years, extensive research has been conducted on the ultrahigh-frequency (UHF) method. Considering that acquiring a partial discharge UHF signal is the first step in a series of tasks, such as fault diagnosis and defect location, the UHF sensor plays an important role in the UHF method. An antipodal Vivaldi antenna installed at a transformer’s joint is designed in this study according to the structural features of 750 kV transformers in China. Several effective structures, such as linear gradient microstrip and slot edge, are employed to improve the return loss and radiation characteristics. A metal box is designed after analyzing the influence of the metal around the antenna. The metal box can effectively shield against electromagnetic interference and does not deteriorate the performance of the antenna significantly. Experimental data show that this antenna is much more sensitive than the rectangular plane spiral antenna. The proposed antipodal Vivaldi antenna is suitable for detecting partial discharge in large transformers.

Investigation of partial discharge between moving charged metal particles and electrodes in insulating oil under flow state and AC condition

Theoretical analysis and experimental study were conducted to clear the partial discharge (PD) between moving charged metal particles and electrodes in insulation oil under flow state and AC condition. The rise time of the PD pulse current is tens of nanoseconds, which is not affected by velocity and voltage. The dominant frequency component of the ultra-high-frequency (UHF) signal due to charged metal particle movement is near 0.39 GHz, which is independent from velocity and voltage. The magnitudes of PD UHF signals are discontinuous and the time of occurrence of PD depends on the trajectories of charged metal particles. PD &-U-N maps clearly indicate that the phase information of the PD UHF signal on the maps is similar regardless of flow velocity and AC condition, but the voltage intensifies the PD and the flow velocity weakens the PD. The trajectories of charged metal particles in the horizontal transformer oil tract were investigated through stress analysis of charged metal particles under flow state and AC voltage. When charged metal particles move along the oil tract under the oil flow, reciprocating oscillation simultaneously occurs in the vertical direction.

A Transformer Partial Discharge Measurement System Based on Fluorescent Fiber

Based on the physical phenomena of optical effects produced by the partial discharge (PD) and on the characteristics of fluorescent fiber sensing of weak fluorescent signals, a PD measurement system using a fluorescent fiber sensor was designed. The main parameters of the sensing system were calculated, an experimental testing platform for PD simulation in the lab was established, and PD signals were then detected through ultra-high frequency (UHF) and optical methods under a needle-plate discharge model. PD optical pulses in transformer oil contained signal-peak and multi-peak pulse waveforms. Compared with UHF detection results, the number of PD pulses and the elapsed PD pulse phase time revealed a good corresponding relationship. However, PD signal amplitudes presented the opposite, thus indicating that PD UHF signals reflected pulse amplitude value, whereas PD optical signals reflected pulse energy magnitude. The n-u-φ three-dimensional distributions indicated that most of the PD signals concentrated in the nearby industrial frequency voltage peak value. Overall, the proposed fluorescent fiber sensing system design can be used successfully in transformer PD signal detection.

Application of Complex Wavelet Transform to Suppress White Noise in GIS UHF PD Signals

During online partial discharge (PD), ultra-high-frequency (UHF) detection of gas-insulated switchgear (GIS), obtaining acceptable levels of sensitivity, still continues to remain a very challenging task, primarily due to strong electromagnetic interference (including white-noise, random, discrete spectral, and stochastic pulses). As white-noise interference stands in the breach existing in GIS PD UHF detection inevitably, the available suppression methods are unsatisfactory. According to the feature of white noise, the Daubechie's complex wavelet is constructed. Through the simple information (SI) and combined information (CI) of the complex wavelet transform (CWT), the denoising method of simulation signals and field signals of PD UHF is studied by the authors. In view of the estimation parameters, the results manifest that white-noise in GIS PD UHF signals can be suppressed effectively by the SI and CI of the CWT.