Ultra-high Frequency Signals Research Articles

Chromatic processing for feature extraction of PD-induced UHF signals in GIS

Partial discharge (PD) detection is an effective means of discovering insulation faults in gas-insulated switchgear (GIS). One of the most extensively used methods in PD detection has historically been the ultrahigh frequency (UHF) method. This study evaluates the chromatic processing methodology and its key factors for feature extraction of UHF signals in GIS. Three types of artificial defects are installed in the GIS tank at 0°, 90°, and 180°, respectively. The features of the UHF signals are extracted in the chromatic space, and PD discrimination of the defects is achieved. The influences of processors are studied before the feature selections are suggested. The time-stepping method is proposed to determine the rules of UHF signal frequency characteristics that vary with time. Finally, the process and options of the chromatics-inspired methodology are summarized.

Intelligent learning approach for UHF partial discharge localisation in air‐insulated substations

To achieve comprehensive insulation deterioration motoring of power equipment and early fault warning in air-insulated substations, a data-driven partial discharge (PD) source localisation method employing noisy ultra-high frequency (UHF) received signal strength indicator (RSSI) and particle filter is proposed in this study. Compared with the existing UHF time-difference-based techniques, UHF wireless sensor arrays and RSSI-based methods provide an economical and high-adaptability solution. However, owing to the multi-pathing and shadowing effects, UHF signal attenuation cannot be modelled. Therefore, a Kalman filter was employed to smoothen the RSSI signal. Furthermore, a semi-parametric regression model is proposed to achieve a more accurate relationship between the RSSI and the transmission distance. Finally, in contrast to traditional localisation algorithms directly based on the RSSI ranging model, a particle filter was used to achieve higher accuracy. It predicted the best distribution of the position of PD by learning and considering all the system states of the previous moment. The laboratory test was performed within an area of 6 m × 6 m, and the results demonstrate that the mean PD source localisation error was 1.16 m, which gives a potential application for the identification of power equipment with insulation deterioration in a substation, while the accuracy is still needed to be verified further by field tests.

A Study on the Extraction Method of Partial Discharge Features in Gas Insulated Switchgear Based on Ultra-High Frequency Signal Envelope

Because the UHF detection method has the advantages of wide detection range and high sensitivity, it is of great significance for partial discharge detection and defect type identification in gas insulated electrical equipment. Therefore, this paper proposes a new type of partial discharge UHF signal pattern recognition algorithm, which can effectively identify the type of partial discharge defects. The low frequency signal modulated by high frequency signal is demodulated by Hilbert transform. This paper presents a method to extract the time domain characteristics of UHF signals emitted by gas insulated switchgears (GIS) partial discharge (PD). By using the Hilbert transform, the envelope of partial discharge signal can be obtained, and then the key points related to features in time domain can be obtained. The artificial insulation fault test platform is developed. Experimental data of three typical partial discharge signals are obtained, and the algorithm is analyzed and verified. The result shows that the method can recognize different types of PD well. So it is practical and effective.

Research on Fading Characteristics of Ultrahigh Frequency Signals in Karst Landform Around Radio Quiet Zone of FAST

AbstractUltrahigh frequency wireless signals are mainly influenced by the geomorphological environment during the transmission process, resulting in fading channels, especially in mountainous regions. The experiment was conducted in the Karst landform of Guizhou Province, China, in order to explore fading distribution characteristics for mainly analyzing electro magnetic compatibility (EMC) specialties between Five‐hundred‐meter Aperture Spherical Radio Telescope (FAST) and wireless radiation equipment around radio quiet zone of this telescope. Based on the channel variation data of six frequencies, which are mainly used by the electrical and electronic equipment of public facilities around FAST, the fading distribution was analyzed by using the Kolmogorov‐Smirnov statistic method. And finally we determined the optimal distribution model with the fading range, fading depth, and fading rate. The results show that (1) the polarization type and signal frequency have a definite influence on the fading distribution types in the Karst landform; (2) Rice distribution is the optimal and stable distribution model in the Karst landform, and the log‐normal distribution model is proposed to characterize the Rice K‐factor distribution; and (3) the line‐of‐sight (LoS) components of the normalized envelopes are 0.6837, 0.8939, 0.5963, 0.6332, 0.5516, and 0.4806. And the multipath scattered components of those are 0.2134, 0.0630, 0.2436, 0.2224, 0.2678, and 0.2880. The research results provide a potential support for the deployment and optimization of wireless communication networks in Karst landform, especially around radio quiet zone of FAST.

Study of the Influence of Winding and Sensor Design on Ultra-High Frequency Partial Discharge Signals in Power Transformers.

Ultra-high frequency (UHF) partial discharge (PD) measurements in power transformers are becoming popular because of the advantages of the method. Therefore, it is necessary to improve the basic understanding of the propagation of signals inside the transformer tank and the factors that influence the sensitivity of the measurement. Since the winding represents a major obstacle to the propagation of the UHF signals, it is necessary to study the effect of winding design on signal propagation. Previous research activities have studied these effects using simplified models, and it is essential to consider the complexity of propagation in a complete transformer tank. Additionally, the quality of UHF PD measurements depends, to a large extent, on the sensitivity of the UHF sensors. In this contribution, a simulation model consisting of a simple, grounded enclosure with multiple winding designs is used to study the propagation characteristics of UHF signals when an artificial PD source is placed inside the winding. After analysis of the results, the winding designs are incorporated in an existing and validated simulation model of a 420 kV power transformer and analyzed to observe the influence in a more complex structure. Two commonly used sensor designs are also used in the simulation model to receive the signals. In all cases, the propagation and signal characteristics are analyzed and compared to determine the influence of the winding and sensor design on the UHF signals. It is found that the level of detail of winding design has a significant impact on the propagation characteristics. However, the attenuation characteristics of the UHF signals received by the two sensor designs are similar, with the electric field distribution around the sensor being the key difference.

A multi frequency point broadband compound antenna for partial discharge detection in gas insulated switchgear

In order to meet the requirements of the miniaturized and wide-band antennas for ultra-high frequency (UHF) detection method, a multi frequency point broadband compound antenna for detecting partial discharges (PD) of gas insulated substations (GIS) was designed. Firstly, through the analysis of the principle of miniaturization and broadbandization of the compound antenna, the meander technology was used to realize the miniaturization of the antenna, the multiple radiation unit technology was used to broaden the detection frequency band of the antenna, and the HFSS simulation software was used to simulate the design of the compound antenna. Then we made the antenna object according to the optimized simulation results, and the voltage standing wave ratio (VSWR) of this antenna was tested by vector network analyzer. Finally, the GIS PD test system was built in the laboratory to conduct the actual measurement research on the antenna. The test results show that: The compound antenna has the characteristics of miniaturization, high gain and multi-band. In the frequency range of 1.0 GHz to 3.0 GHz, its VSWR is less than 2, has a wide frequency range, can record most of the PD information. With the increase of frequency, the compound antenna gain is gradually increasing, and the maximum gain of the antenna can reach 6.5 dB, which can effectively receive weak UHF signals. The proposed antenna is quite promising for PD on-line detection applications.

UHF LS Peano fractal antenna for PD GIS detection

An LS Peano fractal antenna, which integrates the self-similarity and spatial filling features of fractal technology, was designed for detecting the ultra-high frequency (UHF) signals generated by gas-insulated switchgear (GIS) partial discharge (PD). Firstly, we used ANSYS HFSS to simulate and design the LS Peano fractal antenna. Then we made the antenna object according to the optimised simulation results. Finally, PD trials involving a metal protrusion defect are conducted therewith. The test results show that: the LS Peano fractal antenna has ellipsoidal directivity; the measured results indicate that the voltage standing wave ratio (VSWR) of this antenna is less than 4.5 in the range from 300 MHz to 3 GHz, which has better PD monitoring ability; the VSWR of this antenna is less than 2 in the range from 1.1 GHz MHz to 3 GHz, which has a higher density of monitoring PD.

Study on the combined characteristics of UHF and optical signals induced by partial discharge at spacer surface in GIS

In this study, to improve the sensitivity and accuracy of the detection of surface partial discharge (PD) in gas insulation switchgears (GISs), a combination of ultra-high frequency (UHF) and optical methods is proposed based on an integrated sensor. The PD triggered by a fixed metal needle defect attached to the spacer is detected from PD inception to flashover in a real GIS. The characteristics of UHF and optical signals under different applied voltages are compared and analysed in terms of PD waveform, Phase Resolved Partial Discharge (PRPD) pattern, PD count and amplitude. The results show that the surface discharge process can be precisely divided into three stages according to the combined characteristics of the UHF and optical signals. The comparison of the two detection methods shows that the optical method can detect the weak avalanche PD under low voltage while UHF cannot, so it can detect more PDs than UHF method in an AC cycle. In addition, with the deterioration of solid insulation material, the amplitude of the optical signal increases significantly while the amplitude of the UHF signal only increases slightly.

Study on the mixing and separation of UHF signals with multiple insulation defects in GIS

In order to explore the mixing characteristics of ultra-high frequency (UHF) partial discharge (PD) signals in GIS, simulation tools and Antenna Theory concerning the electromagnetic field (XFDTD) have been adopted in investigating the mixed features of UHF signals in GIS environment. Simulation results and theoretical analysis in this paper demonstrate that convolution is the basic relationship between PD current signal and the single UHF PD signal; the PD mixing signals are the linear and instantaneous mixture of single PD signals and they are also the linear and convolution mixture of PD current signals. The reverse process of those mixing modes are also been discussed based on blind sources separation and find out that it is an over complete blind source separation problem to gain single UHF PD signal from mixed one. Moreover, it can be approximated to conventional blind source separation when the layout of ultra-high frequency sensors is compact.

On-Line Partial Discharge Monitoring System for Power Transformers Based on the Simultaneous Detection of High Frequency, Ultra-High Frequency, and Acoustic Emission Signals

The article presents a novel on-line partial discharge (PD) monitoring system for power transformers, whose functioning is based on the simultaneous use of three unconventional methods of PD detection: high-frequency (HF), ultra-high frequency (UHF), and acoustic emission (AE). It is the first monitoring system equipped in an active dielectric window (ADW), which is a combined ultrasonic and electromagnetic PD sensor. The article discusses in detail the process of designing and building individual modules of hardware and software layers of the system, wherein the most attention was paid to the PD sensors, i.e., meandered planar inverted-F antenna (MPIFA), high-frequency current transformer (HFCT), and active dielectric window with ultrasonic transducer, which were optimized for detection of PDs occurring in oil-paper insulation. The prototype of the hybrid monitoring system was first checked on a 330 MVA large power transformer during the induced voltage test with partial discharge measurement (IVPD). Next, it was installed on a 31.5 MVA substation power transformer and integrated according to the standard IEC 61850 with SCADA (Supervisory Control and Data Acquisition) system registering voltage, active power, and oil temperature of the monitored unit. The obtained results showed high sensitivity of the manufactured PD sensors as well as the advantages of the simultaneous use of three techniques of PD detection and the possibility of discharge parameter correlation with other power transformer parameters.

A Method for Separating Multisource Partial Discharges in a Substation Based on Selected Bispectra of UHF Signals

A method for separating multisource partial discharges (PDs) in a substation is proposed based on selected bispectra of ultrahigh frequency (UHF) electromagnetic waves. Bispectra are sensitive to Gaussian noises and processes of symmetrical distribution. The phase information contained in bispectra can be useful and important for further signal processing. Bifrequencies where Fisher-like class separability measures between signals’ bispectra achieve their maximums are selected as characteristic parameters of the signals. Then, the selected bispectra are utilized for training the radial basis neural network to separate PD UHF signals in a substation. The method is used to analyze simulated UHF signals mixed with Gaussian white noise and frequency-fixed interference, and to separate PD UHF signals that are collected in a 500 kV substation. In order to prove the validity of the proposed separation method, the localization results are compared with the results calculated by time delay sequence, and the proposed separating algorithm is verified in the interference circumstances of a substation. However, the exact location of PD sources cannot be calculated according to the time delay sequence when the PD sources in a substation are close to each other or there are fewer than four antennas for receiving signals.

Analysis of Plasma Irregularities on a Range of Scintillation‐Scales Using the Resolute Bay Incoherent Scatter Radars

AbstractScintillation in the polar cap ionosphere is observed with a Coherent Electromagnetic Radio Tomography (CERTO) receiver while the Resolute Bay Incoherent Scatter Radars (RISR) provide background plasma conditions in a 3D volume. We interpret fluctuations in the very high frequency (VHF) and ultrahigh frequency (UHF) signal associated with mid‐scale ionospheric structuring using 3D density gradients and plasma drift velocity vectors and calculate the maximum gradient drift instability growth rate. Plasma structuring is evident for any plasma density gradient, but sub‐kilometer structures are less likely on the leading edge of polar patches, possibly due to a much faster diffusion rate for small‐scale structures. Structures are much more uniformly distributed around density enhancements that do not have clear leading and trailing edges. Although the gradient drift instability is an important factor in polar cap structuring, linear growth rates are most successful at predicting structuring around isolated density enhancements in consistent plasma flows. For more general density gradients, the time history of a plasma parcel and local diffusion rates must also be considered.

Simultaneous radial deformation and partial discharge detection of high‐voltage winding of power transformer

Condition monitoring of power transformers has attracted a lot of attention due to their important roles in determining power system reliability. Radial deformation of power transformer winding should be monitored online to prevent more damages to winding and possible transformer outage. The ultra-high-frequency (UHF) stepped-frequency synthetic-aperture radar imaging method has recently been proposed as an online method for high-voltage winding radial deformation detection. On the other hand, partial discharge (PD) as another defect of the transformer winding propagates UHF signals in the transformer environment, which should be detected online. In this study, the practical application of a designed monitoring system is investigated for simultaneous online detection of both PD and radial deformation defects in a real three-phase power transformer. In addition, radial deformation is localised through a monitoring system designed based on the proposed method. Using this system, only one set of antennas is needed to detect both defects which lead to reducing the number of installed antennas and economic application of the monitoring system.

A new sliding discrete Fourier transform phase difference measurement method for extreme frequency signals.

While there are many ultralow frequency signals and ultrahigh frequency signals in the vibration engineering field, the existing discrete Fourier transform (DFT) spectrum analysis methods bring about significant phase difference errors when measuring these extreme frequency signals. In order to improve the performance of these methods, a new sliding DFT phase difference measurement method for extreme frequency signals is proposed. First, the spectrum of extreme frequency signals is analyzed, which is used to illuminate the contribution of negative frequency. Then, the spectrum leakage is restrained by adopting rectangular self-convolution windows (RSCWs). Finally, the sliding recursive algorithm is introduced to reduce the computational load. The whole processes of formula derivation for phase difference measurement by adopting different RSCWs are described in detail. Simulations show that the proposed method obtains a better real time characteristic and a higher phase difference measurement precision than conventional DFT methods, which is suitable especially for extreme frequency vibration signals.

Quantitative Analysis of the Sensitivity of UHF Sensor Positions on a 420 kV Power Transformer Based on Electromagnetic Simulation

With an increasing interest in ultra-high frequency (UHF) partial discharge (PD) measurements for the continuous monitoring of power transformers, it is necessary to know where to place the UHF sensors on the tank wall. Placing a sensor in an area with many obstructions may lead to a decrease in sensitivity to the UHF signals. In this contribution, a previously validated simulation model of a three-phase 300 MVA, 420 kV power transformer is used to perform a sensitivity analysis to determine the most sensitive sensor positions on the tank wall when PD activity occurs inside the windings. A matrix of UHF sensors located on the transformer tank is used to perform the sensitivity analysis. Some of the windings are designed as layer windings, thus preventing the UHF signals from traveling through them and creating a realistic situation with very indirect propagation from source to sensor. Based on these findings, sensor configurations optimized for UHF signal sensitivity, which is also required for PD source localization, are recommended for localization purposes. Additionally, the propagation and attenuation of the UHF signals inside the windings and the tank are discussed in both oil and air.

Investigation on the dielectric performance of titania nanoparticles and surfactant added mixture of mineral and natural ester oil

The optimum quantity of titania nanoparticles as a filler and the surfactant ought to be added with a mixture of 20% ester oil and 80% transformer oil, which is estimated based on Corona Inception Voltage (CIV) and breakdown studies under AC and DC voltages. The addition of titania nanoparticles along with cetyltrimethylammonium bromide (CTAB) as a surfactant to mixed oil is compared with nanofluid prepared with oleic acid as a surfactant. The breakdown voltage is high under lightning impulse voltage followed by DC and AC voltages. Ultra High Frequency (UHF) signal radiated during corona activity has shown discharge magnitude less with CTAB added nanofluid. The phase-resolved partial discharge studies have indicated less spread in phase discharges with nanofluid formed with CTAB. Particle Size Distribution (PSD) studies, Zeta potential, and dielectric parameter measurements have corroborated the superiority of CTAB used as a surfactant for optimized mixed oil, which is also supported by flow electrification studies. UV and fluorescence spectra of the samples were analyzed to substantiate the influence of nanoparticles on the chemical signature of oil. It is observed that optimally dispersed nanofluid exhibits better thermal conductivity, turbidity, and flashpoint. The presence of nanoparticles exerted marginal effects on viscosity of the fluid, but no variation is observed after electrical breakdown in nanofluids, ensuring its stability.

Understanding the dielectric and mechanical properties of self‐passivated Al–epoxy nanocomposites

Epoxy nano passivated aluminium composites with optimised size and filler contents were fabricated. Variation in contact angle and surface roughness is insignificant with increasing filler into nanocomposites but it showed a drastic reduction on corona ageing. Water droplet initiated corona inception voltage (CIV) is high under the negative DC voltage followed with positive DC and AC voltages. The bandwidth of ultra-high frequency signal generated due to water droplet initiated corona discharge lies in the range of 0.5–1.2 GHz. Surface potential measurements have shown that the decay in the potential was fast initially, and it became slower and sluggish subsequently. The trap energy density versus trap depth plot exhibits shallow traps and deep traps at around 0.8 and 0.87 eV, respectively. Permittivity, conductivity and loss factor have increased with an increase in the filler content in nanocomposites. The bulk resistance and capacitance of samples were determined for obtaining the equivalent parallel RC circuit model. Incorporation of nanofillers increases the glass transition temperature and reduces the tan δ with increasing frequencies as evident from dynamic mechanical analysis studies. A direct correlation is observed between the plasma temperature measured through laser-induced breakdown spectroscopy spectra and hardness of the material.

A Novel Partial Discharge Detection Method Based on the Photoelectric Fusion Pattern in GIL

Optical detection and ultrahigh frequency (UHF) detection are two significant methods of partial discharge (PD) detection in the gas-insulated transmission lines (GIL), however, there is a phenomenon of signals loss when using two types of detections to monitor PD signals of different defects, such as needle defect and free particle defect. This makes the optical and UHF signals not correspond strictly to the actual PD signals, and therefore the characteristic information of optical PD patterns and UHF PD patterns is incomplete which reduces the accuracy of the pattern recognition. Therefore, an image fusion algorithm based on improved non-subsampled contourlet transform (NSCT) is proposed in this study. The optical pattern is fused with the UHF pattern to achieve the complementarity of the two detection methods, avoiding the PD signals loss of different defects. By constructing the experimental platform of optical-UHF integrated detection for GIL, phase-resolved partial discharge (PRPD) patterns of three defects were obtained. After that, the image fusion algorithm based on the local entropy and the phase congruency was used to produce the photoelectric fusion PD pattern. Before the pattern recognition, 28 characteristic parameters are extracted from the photoelectric fusion pattern, and then the dimension of the feature space is reduced to eight by the principal component analysis. Finally, three kinds of classifiers, including the linear discriminant analysis (LDA), support vector machine (SVM), and k-nearest neighbor (KNN), are used for the pattern recognition. The results show that the recognition rate of all the photoelectric fusion pattern under different classifiers is higher than that of optical and UHF patterns, up to the maximum of 95%. Moreover, the photoelectric fusion pattern not only greatly improves the recognition rate of the needle defect and the free particle defect, but the recognition accuracy of the floating defect is also slightly improved.

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.

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.