Ultra-high Frequency Partial Discharge Research Articles

RSSI-Power-Based Direction of Arrival Estimation of Partial Discharges in Substations

The localization of partial discharges in air-insulated substations using ultra-high frequency technology is widely studied for power equipment early warning purposes. Ultra-high frequency partial discharge localization systems are usually based on the time-difference of electromagnetic wave signals. However, the large size of test equipment and the need for a high sampling rate and time synchronization accuracy limit their practical application. To address this challenge, this paper proposes a power-based partial discharge direction of arrival method using a received signal strength indicator from an ultra-high frequency wireless sensor array. Furthermore, the Gaussian mixture model is used for noise suppression, and the Gaussian process classifier is used for line of sight received signal strength indicator data identification. Laboratory tests are performed and the results show the average error of direction of arrival is less than 5°. The results verify the effectiveness of the proposed partial discharge localization system.

Calibration Proposal for UHF Partial Discharge Measurements at Power Transformers

The continuous, non-intermitted service of electrical grids relies on the reliability of their assets, e.g., power transformers. Local insulation defects can result in serve failures such as breakdowns with severe subsequent costs. The prevention of such events is crucial. Hence, partial discharge (PD) activity at power transformers is evaluated directly in the factory before shipment. Additionally, PD activity can be monitored during service using the ultra-high frequency (UHF) method. In this contribution, a calibration procedure is proposed for the UHF method. The calibration process is required to ensure both, reproducibility and comparability of UHF measurements: Only a calibrated UHF measurement procedure can be introduced supplementary to IEC 60270 in acceptance tests of power transformers. The proposed calibration method considers two factors: The influence of the UHF-antenna’s sensitivity and the PD recorder characteristics including accessories such as cable damping, pre-amplifier, etc. The former is addressed by a characterization of UHF sensors using the standard antenna factor (AF) in a gigahertz transverse electromagnetic (GTEM) cell. The PD recorder’s influence is corrected by using a defined, invariable test signal as reference for all recording devices. A practical evaluation of the proposed calibration procedure is performed in a laboratory setup using different UHF recording devices and UHF sensors using artificial PD signals and real voltage-driven PD sources.

UHF Partial Discharge Location in Power Transformers via Solution of the Maxwell Equations in a Computational Environment

This paper presents an algorithm for the localisation of partial discharge (PD) sources in power transformers based on the electromagnetic waves radiated by a PD pulse. The proposed algorithm is more accurate than existing methods, since it considers the effects of the reflection, refractions and diffractions undergone by the ultra-high frequency (UHF) signal within the equipment tank. The proposed method uses computational simulations of the electromagnetic waves generated by PD, and obtains the time delay of the signal between each point in the 3D space and the UHF sensors. The calculated signals can be compared with the signals measured in the field, so that the position of the PD source can be located based on the best correlation between the simulated propagation delay and the measured data. The equations used in the proposed method are defined as a 3D optimisation problem, so that the binary particle swarm optimisation algorithm can be used. To test and demonstrate the proposed algorithm, computational simulations were performed. The solutions were sufficient to identify not only the occurrence of defects, but also the winding and the region (top, centre or base) in which the defect occurred. In all cases, an accuracy of greater than 15 cm was obtained for the location, in a 180 MVA three-phase transformer.

Design and Implementation of Microstrip Patch Ultra-wide Band Antenna for Detection of UHF Partial Discharge

Partial discharge (PD) is an electrical release or spark that occurs between two conducting electrodes that are not bridging, and it can occur at any points in the insulation system. PDs emit electromagnetic field radiation in the frequency range of 300 MHz to 1.5 GHz. Thus, it is more appropriate to detect and monitor partial discharge using an ultra-wideband antenna which offers more accuracy than the narrowband antenna. This paper proposes the design and implementation of a microstrip patch antenna which has been designed to possess wider detection performance of ultra-high frequency (UHF) PD signal. The PD spectra of the designed UWB antenna and the commercial whip antenna was compared and analyzed. The result shows that the UWB antenna can effectively detect the UHF PD signals that occur between two electrodes. As results, it is implied that PD measurement by using designed UWB antenna is found to suitable to detect the PD signals for online monitoring of high voltage equipment.

Combined Characterization of Free-Moving Particles in HVDC-GIS Using UHF PD, High-Speed Imaging, and Pulse-Sequence Analysis

Reliable operation of high-voltage equipment depends on defect-free HV insulation systems. However, defects in the insulation can lead to partial discharge (PD) activity. PD measurement has been shown to be a useful tool for evaluating the condition of high voltage components including gas-insulated switchgear (GIS). This work focuses on characterizing the motion and PD signal behavior of free-moving particles in an experimental GIS arrangement under high dc field stress. For this purpose, the particle geometry, material composition, and amplitude of the applied negative dc voltage are varied. PD signals are measured using a broadband ultra-high-frequency (UHF) sensor and recorded in the time domain. The UHF signal is used to trigger a synchronized high-speed camera in order to observe the correlation between particle motion and UHF PD pulse activity. Certain unique combinations of UHF pulse repetition rates and signal amplitudes in the time domain are observed that depended on and were correlated with particles’ motion. These are evaluated by means of pulse sequence analysis, whose significant clusters enable estimation of particle motion. In particular, particle motion with small hopping amplitudes on the negative electrode—known as “firefly”—is differentiated with high accuracy.

Partial Discharge Angle of Arrival Estimation Using UHF Wireless Sensor Array

The detection and localization of partial discharge (PD) in air-insulated substations by ultra-high frequency (UHF) technology is widely studied. Existing UHF PD localization system mainly focus on time-difference of UHF signal, which requires very high synchronized sampling rate. This paper proposes a received signal strength (RSS) based angle of arrival (AoA) method by a circle UHF wireless sensor array. An AoA estimation scheme is derived through the radiation pattern of designed UHF antenna. Interpolation and neural network are applied to improve the AOA resolution. A field test is performed to verify the effectiveness of the proposed PD localization system. The results show that the estimated error on average is below 7°. Compared to the time-difference-based method, the accuracy of our designed system is more feasible for practical application considering its significant low-cost feature.

A New Denoising Method for UHF PD Signals Using Adaptive VMD and SSA-Based Shrinkage Method.

Noise suppression is one of the key issues for the partial discharge (PD) ultra-high frequency (UHF) method to detect and diagnose the insulation defect of high voltage electrical equipment. However, most existing denoising algorithms are unable to reduce various noises simultaneously. Meanwhile, these methods pay little attention to the feature preservation. To solve this problem, a new denoising method for UHF PD signals is proposed. Firstly, an automatic selection method of mode number for the variational mode decomposition (VMD) is designed to decompose the original signal into a series of band limited intrinsic mode functions (BLIMFs). Then, a kurtosis-based judgement rule is employed to select the effective BLIMFs (eBLIMFs). Next, a singular spectrum analysis (SSA)-based thresholding technique is presented to suppress the residual white noise in each eBLIMF, and the final denoised signal is synthesized by these denoised eBLIMFs. To verify the performance of our method, UHF PD data are collected from the computer simulation, laboratory experiment and a field test, respectively. Particularly, two new evaluation indices are designed for the laboratorial and field data, which consider both the noise suppression and feature preservation. The effectiveness of the proposed approach and its superiority over some traditional methods is demonstrated through these case studies.

Design of Ultra-Wide Band Metal-Mountable Antenna for UHF Partial Discharge Detection

This paper presents an ultra-wideband metal-mountable antenna used in the ultra-highfrequency (UHF) partial discharge (PD) detection. The designed antenna combines a coplanar waveguide antenna and multilayer substrates to effectively broaden its bandwidth when mounted on a conductive surface. These substrates consist of two layers of FR-4 dielectric substrates and two layers of the absorbing gasket, which is adapted to absorb the reflected electromagnetic signals. The parametric study is conducted to optimize antenna performance. A prototype is fabricated to confirm the design, and the measurement results show good agreement with the simulation. When mounted on the metal plate, the proposed antenna covers the UHF bandwidth of 400 MHz-3 GHz for S 11 <; -10 dB with a compact size (282 mm × 242 mm × 8.75 mm). As the thickness of the antenna is only 8.75 mm, the safety distance of electric insulation in electrical equipment will not be affected. A PD experiment has been carried out, and a reference antenna is used in the experiment for comparison. Compared with the conventional antenna, the proposed antenna has a better performance when mounted on the metal plate. It is shown that the designed antenna is a very good candidate for UHF PD detection inside of high-voltage equipment.

Pattern Recognition of Partial Discharge by Using Scale parameters-Energy Entropy Characteristic Pairs

In this paper, the complex wavelet transform (CWT) was used to process the ultra-high frequency partial discharge (UHF PD) signal in gas insulated switchgear (GIS) at different scales. The trend curves of complex wavelet transform energy entropy (CWT-EE) under different decomposition scale were analyzed, and it was found that the PD feature information mainly distributed in the scales, in which the gradient of CWT-EE is big. Besides, The CWT-EE characteristics and their scales were extracted to the structure characteristic pairs for PD type identification. The recognition results show that the characteristic pair could effectively identify four typical defects in GIS and obviously reduce the feature dimension.

Novel Simulation Technique of Electromagnetic Wave Propagation in the Ultra High Frequency Range within Power Transformers.

Diagnoses of power transformers by partial discharge (PD) measurement are effective to prevent dielectric failures of the apparatus. Ultra-high frequency (UHF) method has recently received attention due to its various advantages, such as the robustness against external noise and the capability of PD localization. However, electromagnetic (EM) waves radiated from PD tend to suffer attenuation before arriving at UHF sensors, because active part of the transformer disturbs the EM wave propagation. In some cases, that results in poor detection sensitivity. To understand propagation and attenuation characteristics of EM waves and to evaluate the detection sensitivity quantitatively, a computational approach to simulate the EM wave propagation is important. Although many previous researches have dealt with EM wave simulation for transformers, validations of those simulations by comparing with the experimental ones have seldom been reported. In this paper, cumulative energies, signal amplitudes and propagation times of EM waves were measured using a 630 kVA transformer. EM wave propagation was computed using the time-domain finite integration technique and the results were compared with the experimentally obtained ones. These simulation results showed good agreement with the experimental ones. The results can serve as guidelines to improve the efficiency of UHF PD detection and offer the possibility to achieve optimal placement of UHF sensors in power transformers.

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.

Improving the Error of Time Differences of Arrival on Partial Discharges Measurement in Gas-Insulated Switchgear.

Partial Discharge (PD) detection based on Ultra-High-Frequency (UHF) measurements in Gas-Insulated Switchgear (GIS) is often used for fault location based on extraction of Time Differences of Arrival (TDoA), and the core technique is to obtain the precise time difference of each UHF signal. Usually, TDoA extraction algorithms can be categorized as cross-correlation function method (CCF), minimum energy method (ME), and threshold value method (TV) are not qualified to analyze the time difference with high accuracy and efficiency, especially the complicated UHF PD signals in the field. In this paper, multiple tests were carried out based on the real GIS UHF signals. Three typical algorithms (CCF, ME, and TV) were used to extract and calculate the TDoA of UHF signals. Afterwards, depending on the disassembly of equipment, the accuracy and effective range of the algorithms are analyzed by means of error and variance. To minimize the error and the variance, an average method with the combination (CA) and portfolio of traditional algorithms is proposed and verified in different situations. The results demonstrate that the improved algorithm could increase the accuracy of time difference extraction, less than 4.0%.

Research on Measurement and Evaluation of Ultra High Frequency Partial Discharge Monitoring Device

In order to evaluate the partial discharge Ultra High Frequency (UHF) detection device, the author conducted a laboratory simulation experiment on UHF Partial Discharge (PD) online monitoring system. The UHF signal is simulated by the pulse signal generated by the ns steep pulse generator. By comparing the characteristics of the generated UHF signal with the spectral features detected by the UHF partial discharge on-line monitoring system, the detection capability, pattern recognition ability, and anti-jamming capability of the UHF partial discharge on-line monitoring system are measured and evaluated. Through the research on the testing and evaluation of power equipment, it can ensure the normal operation of the partial discharge online monitoring system.

GIS UHF Partial Discharge On-line Monitoring Device Evaluation

The Ultra-high Frequency (UHF) partial discharge on-line monitoring system device is widely used in gas insulated substations (GIS), and has become one of the important detection methods for partial discharge of GIS. However, due to the lack of uniform standards within the industry, the equipment produced by the manufacturers is uneven, resulting in the performance evaluation problems of the UHF online monitoring device in the purchase and acceptance process. For this question, this paper proposes a measurement method, which has two parts: UHF sensor evaluation and complete device evaluation.A set of evaluation methods was established by using a signal simulation test method and a simulated fault evaluation method, and a more comprehensive understanding of the GIS UHF partial discharge on-line monitoring device were proposed.

Direction of arrival estimation method for multiple UHF partial discharge sources based on virtual array extension

The localization method of multiple partial discharge (PD) of power equipment in airinsulated substation based on traditional ultra-high frequency (UHF) sensor array suffer from the problem of low accuracy, due to the lack of enough sensors. Thus, a novel virtual array extension method based on Compressive Sensing (CS) is proposed in this paper. The traditional 2×2 UHF array is virtually extended to a N×N (N>2) array, with the steering vector matrix as the basis transformation matrix, the random Gaussian matrix as the measurement matrix, and the orthogonal matching pursuit (OMP) algorithm as the signal reconstruction algorithm. The PD signal received by the extended array is used to construct the PD spatial spectrum, on the basis of wide-band signal focusing. The directional angle and pitch angle of PD sources are obtained by performing peak search of the PD spatial spectrum. The simulation results show that the extended 4×4 array can detect up to 3 PD sources simultaneously. Moreover, the directional of arrival (DOA) estimation accuracy is greatly improved. Compared to the traditional 2×2 array, the directional angle estimation error is reduced from 10° to 4°. The experiment results further verified the effectiveness of the proposed method.

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.

UHF partial discharge localization algorithm based on compressed sensing

Partial discharge (PD) localization is an effective way to detect the insulation problem of power equipment. Considering the environmental adaptability and low hardware cost, a novel ultrahigh frequency (UHF) PD localization algorithm based on received signal strength indication (RSSI) fingerprint is proposed. The methodology includes two stages: in the offline, the RSSI fingerprint map is established by filed test and the BP neural network is trained. Particle swarm optimization (PSO) algorithm is also adopted to choose the initial weight of the BP neural network. In the online stage, the PD sources localization which consists of two steps is deployed. Firstly, a preliminary localization achieved by trained BP neural network. Secondly, more accurate localization result is obtained using compressive sensing (CS) algorithm. Furthermore, since the UHF signal is sensitive to the layouts change of detection area, it is necessary to update the fingerprint map timely from practical application point of view, which is also a time-consuming process. To reduce the workload of fingerprint map updating, a reconstruction algorithm based on CS theory is proposed, by which the fingerprint map can be rebuilt by only a subset of original fingerprint data. A filed experiment in the substation is performed and the results show that, the average localization error of the CS algorithm is 0.89 meter and 90.4% localization errors are less than 2 meters. The results proved the accuracy and effectiveness of our proposed localization algorithm.

UHF PD measurement system with scanning and comparing method

Based on the periodic and repetitive characteristics of partial discharge (PD) under power frequency voltage, an ultra-high-frequency (UHF) PD measurement system using scanning and comparing method is realized without analog to digital (A/D) acquisition. The UHF PD pulses are compared with adjustable reference levels by high-speed comparator, and the number of pulses higher than the reference levels is recorded by a field programmable gate array (FPGA) along with corresponding phase information. The phases, amplitudes and number of discharge pulses can be extracted from the acquired data, which is verified in needle-plate PD experiment result analysis. And PD spectrograms of proposed method proves to be highly correlated with that of pulse current method and conditional UHF method. Influence factors in PD signal acquisition process are also analyzed.

Combined diagnosis of partial discharge based on the multi-dimensional characteristic parameters

This paper presents a comprehensive multi-parameter diagnosis method based on multiple partial discharge signals include high-frequency current, ultrasound, ultrahigh frequency (UHF) etc. First, acquire the high-frequency current, ultrasound, UHF partial discharge data under various types of defects, and extract the characteristic values, including nine basic characteristic parameters, eight phase characteristic parameters and the like. Diagnose signals respectively, with the method based on information fusion and semi-supervised learning for high-frequency current PD data, the method based on adaptive mutation parameters of particle entropy for ultrasonic signals, the method based on IIA-ART2A neural network for UHF signals. Then integrate the diagnostic results, which is the probability of fault of various defects and matrix, of different PD diagnosis signals, and analysis with the multiple classifier based on multi-parameter fuzzy integral to get the final diagnosis.

Experimental Research on Relationship between UHF Partial Discharge Signals and Discharge Quantity in GIS

Apparent discharge quantity is usually recognized as judgement standard for severity of partial discharge in the field of electrical equipment insulation diagnosis. In recent years, the ultra-high-frequency (UHF) method has been widely used due to its unique advantages on on-line monitoring and positioning, but the relationship between UHF partial discharge signals and discharge quantity is still a difficult problem of UHF method. In order to research relationship between UHF partial discharge signals and discharge quantity in GIS, a large number of experiments, based on four kinds of typical insulation defects in the GIS, are carried out. Degree of correlation, between parameters including UHF energy, quadratic integral, peak voltage, peak-to-peak value, wave area and discharge quantity, the square of discharge quantity, is studied based on coefficient of determination. The experimental results show there is linear relation between UHF signal energy and the square of discharge quantity with high related degree.