Ultra-high Frequency Sensors Research Articles

Ultra-High Frequency Sensors for Detecting Partial Discharge in Power Cables

Partial discharge (PD) detection is vital for evaluating the health of power cable insulation, where failure can lead to significant disruptions. This study investigates the use of Ultra-High Frequency (UHF) sensors to detect PD signals, which typically occur in nanoseconds. The sensors operate in the GHz range and minimize interference by selecting frequencies above 400 MHz, where background noise is reduced. Through comparison with other detection methods, UHF sensors demonstrate superior sensitivity in measuring minor discharges, providing a reliable means for on-site condition assessment of high-voltage equipment. The study concludes that UHF sensors offer a practical solution for improving PD detection accuracy, particularly in challenging field conditions.

Research on Miniaturized UHF Sensing Technology for PD Detection in Power Equipment Based on Symmetric Cut Theory.

In answer to the demand for high sensitivity and miniaturization of ultra-high frequency (UHF) sensors for partial discharge (PD) detection in power equipment, this paper proposes research on miniaturized UHF-sensing technology for PD detection in power equipment based on symmetric cut theory. The symmetric cut theory is applied for the first time to the miniaturization of PD UHF sensors for power equipment. A planar monopole UHF sensor with a size of only 70 mm × 70 mm × 1.6 mm is developed using an exponential asymptotic feed line approach, which is a 50% size reduction. The frequency-response characteristics of the sensor are simulated, optimized and tested; the results show that the standing wave ratio of the sensor developed in this paper is less than 2 in the frequency band from 427 MHz to 1.54 GHz, and less than 5 in the frequency band from 300 MHz to 1.95 GHz; in the 300 MHz~1.5 GHz band; the maximum and average gains of the sensor E-plane are 4.76 dB and 1.02 dB, respectively. Finally, the PD simulation experiment platform for power equipment is built to test the sensor's sensing performance; the results show that the sensor can effectively detect the PD signals; the sensing sensitivity is improved by about 95% relative to an elliptical monopole UHF sensor.

Partial Discharge Pattern Recognition Based on an Ensembled Simple Convolutional Neural Network and a Quadratic Support Vector Machine

Partial discharge (PD) is a crucial and intricate electrical occurrence observed in various types of electrical equipment. Identifying and characterizing PDs is essential for upholding the integrity and reliability of electrical assets. This paper proposes an ensemble methodology aiming to strike a balance between the model complexity and the predictive performance in PD pattern recognition. A simple convolutional neural network (SCNN) was constructed to efficiently decrease the model parameters (quantities). A quadratic support vector machine (QSVM) was established and ensembled with the SCNN model to effectively improve the PD recognition accuracy. The input for QSVM consisted of the circular local binary pattern (CLBP) extracted from the enhanced image. A testing prototype with three types of PD was constructed and 3D phase-resolved pulse sequence (PRPS) spectrograms were measured and recorded by ultra-high frequency (UHF) sensors. The proposed methodology was compared with three existing lightweight CNNs. The experiment results from the collected dataset emphasize the benefits of the proposed method, showcasing its advantages in high recognition accuracy and relatively few mode parameters, thereby rendering it more suitable for PD pattern recognition on resource-constrained devices.

On-Line Partial Discharge Monitoring System for Switchgears Based on the Detection of UHF Signals

Aiming at the phenomenon of partial discharge caused by the insulation fault of switchgears, an ultra-high frequency (UHF) partial discharge online monitoring system based on the Internet of Thing (IoT) is designed. The hardware of the system mainly consists of UHF sensors, signal conditioning circuits, and data acquisition circuits to realize the monitoring of the discharge signal. The monitoring data is uploaded to the cloud platform through the 4G DTU module, and the host computer software based on B/S architecture is designed on the server side, which can monitor the operation status of the switchgear anytime and anywhere. The experimental results show that the detection system is stable and reliable and can meet practical needs.

Partial Discharge Wideband Full-Band High-Gain Resonant Cavity UHF Sensor Research.

To meet the real demand for broadband full-band high-gain antenna sensors in the process of partial discharge (PD) Ultra-High frequency (UHF) detection test and online monitoring of power equipment, this paper builds a resonant cavity monopole UHF antenna sensor based on Fabry-Perot resonant cavity antenna technology, conducts the sensor Voltage Standing Wave Ratio (VSWR) optimization study using curved flow technology, conducts the sensor gain optimization study using slot dual resonant structure, and, finally, tests the sensor performance using the built PD detection test platform. The resonant cavity monopole antenna exhibits outstanding VSWR performance in the frequency range of 0.37 GHz-3 GHz, according to simulation and test data: the average gain in the frequency range of 0.3 GHz-3 GHz is 4.92 dBi, and the highest gain at the primary resonant frequency of 1.0 GHz is 7.16 dBi, with good radiation performance over the whole frequency spectrum. The electromagnetic pulse signal sensed by the UHF sensor developed in this paper can demonstrate the energy spectrum distribution characteristics of PD radiation electromagnetic wave signal more comprehensively, laying a firm technical foundation for thoroughly understanding the electromagnetic wave radiation characteristics of various types of PD insulation defects of various power equipment and the selection of a specific direction for its supporting optimization.

Planar Sensor for Noise Cancellation During Partial Discharge Detection in Open Substation

In compliance with next-generation high-voltage substations, ultra-high frequency (UHF) planar sensors are becoming more popular than ever for their online features in partial discharge (PD) diagnostics. However, PD signals mixing with different noises still exists as a major challenge for UHF sensors. Especially in open substations, telecommunication interferences become predominant noise sources to an external UHF sensor placed outside of the equipment chamber. Despite band-stop filters are additionally connected to UHF sensors for de-noising, the inherent noise cancellation mechanism is not yet found in any UHF sensor. With the best of our knowledge and survey, we are the first to introduce here a planar sensor that inherently eliminates telecommunication interferences during PD detection for open substations even without using any post-processing filters. To design our sensor, we have applied techniques of truncated partial ground plane for wideband characteristics and modified radiating patch for enhanced gain performance. A novel intermingled coupling resonator is designed to remove the GSM-900 band from within the sensor bandwidth. We have tested our prototype both for the free-space propagation and PD detection performances. The prototype has a compact physical size of 16×8 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and an operational bandwidth within 792-1414 MHz. For a surface discharge source, the prototype successfully detects the PD signals at the earliest stage. Our prototype minimizes the ambient noise-floor to 2.5 mV and improves the signal-to-noise ratio by more than 27.9 dB which is relatively higher than conventional UHF sensors. The proposed sensor also has potentials of classifying PD sources.

Locating Partial Discharges in Power Transformers with Convolutional Iterative Filtering.

The most common source of transformer failure is in the insulation, and the most prevalent warning signal for insulation weakness is partial discharge (PD). Locating the positions of these partial discharges would help repair the transformer to prevent failures. This work investigates algorithms that could be deployed to locate the position of a PD event using data from ultra-high frequency (UHF) sensors inside the transformer. These algorithms typically proceed in two steps: first determining the signal arrival time, and then locating the position based on time differences. This paper reviews available methods for each task and then propose new algorithms: a convolutional iterative filter with thresholding (CIFT) to determine the signal arrival time and a reference table of travel times to resolve the source location. The effectiveness of these algorithms are tested with a set of laboratory-triggered PD events and two sets of simulated PD events inside transformers in production use. Tests show the new approach provides more accurate locations than the best-known data analysis algorithms, and the difference is particularly large, 3.7X, when the signal sources are far from sensors.

Machine Learning Approach to RFID Enabled Health Monitoring of Coal Mine Conveyor Belt

The mining conveyor belt is an imperative component of the mine industry which serves the crucial role of transporting materials. Predicament such as conveyor belt cracks has to be avoided, because any potential cause of conveyor belt failure constitutes risk of fatalities and significant economic implications. Hence, a new crack detection method is developed which can duly alert prior to any inception of failure. The research incorporates an interdigital capacitor (IC) based Ultra High Frequency (UHF) radio frequency identification (RFID) tag as sensor and Machine Learning (ML) to monitor the formation of cracks. This is done by collecting data from the UHF sensor when it is placed on a conveyor belt. Two states of the conveyor belt are investigated -stationary and a travelling belt moving at speeds between 1-5 m/s. For the case of motion, it is successfully replicated with the help of an electrical treadmill. By using ML integration, the outcomes will be more effective in tracking crack features. The model is tested with different types of inputs, followed by classification based on experimental data. This method results in a very accurate determination of cracks, crack orientation and width. The experimental model is 97.2% accurate in identifying the presence of cracks and 93.9% accurate in detecting their orientation; it can also determine half a millimetre-wide crack width with 97% of accuracy. This detection system is extremely accurate, even when there is movement. The achieved detection rate of 99.4% depicts the effectiveness of the model performance by successfully combating the interferences caused by motion. This research is intended to be a stepping stone towards an efficient remote health monitoring (HM) system suitable for the smart future.

External UHF Sensor for GIS PD Insulation Defect from Resin Hole

In view of the effective perception demand of PD (Partial Discharge) insulation defect of in-service GIS (Gas Insulated Switchgear), the external UHF (Ultra High Frequency, 0.3−3 GHz) sensing technology for GIS PD insulation defect from resin hole is studied in this paper. Firstly, rectangular waveguide theory is used to analyze the electromagnetic wave propagation characteristics from rectangular resin hole in GIS disc insulator. It is found that the energy of leaked electromagnetic wave mainly concentrates in the frequency band above 1 GHz. Then based on this frequency band characteristics, a cavity-backed bowtie sensor for GIS PD external detection is designed optimized by HFSS finite element software, in band of 1–3 GHz, its maximum VSWR is 7, the minimum is 1.1, the average is 2.9, and in band of 0.3–1 GHz, the maximum and minimum VSWR is 42.8 and 7, the average is 20.6. Finally, a sensor prototype is made, its sensitivity experiment is carried out on 220 kV GIS, experimental results show that the designed sensor can stably detect the PD electromagnetic wave signal leaked from the resin hole, and the signal energy in frequency band range is consistent with the theoretical analysis results.

Understanding the Electro-Rheological Aspects of Nano Silica Based Ester Fluid With Surfactants and Deep Learning-Based Prediction of ECT

The present study deals with understanding the impact of different surfactants with nano-silica based ester fluid on its electrical and rheological properties. The stability of nanofluid is of prime concerns, which is achieved by the inclusion of ionic and non-ionic surfactants viz. cetyl trimethyl ammonium bromide (CTAB), oleic acid and Span-80. It is observed that CTAB as surfactant has shown discharge resistance property along with high breakdown strength enhancement of up to 39.5% with ester nanofluid. It is observed that fluorescent fiber technique is more sensitive to identify the inception of corona discharge as compared to Ultra high frequency sensor. The permittivity and tan <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\delta $ </tex-math></inline-formula> of the fluid have shown marginal increase with the addition of surfactants, irrespective of temperature of the fluid. Rheological properties of the liquid showed only Newtonian flow behaviour even upon inclusion of the surfactant. The viscosity of the base fluid and the nanofluids exhibits similar decay rate at higher temperatures. Electrostatic charging tendency (ECT) derives the correlation between rotation speed and the static current measured adopting spinning disc technique. In addition, the performance of Long Short-Term Memory (LSTM) model is efficient compared to Artificial Neural Network (ANN) model adopted in predicting the charging tendency incorporating electro-rheological parameters at distinct temperatures. The electrical and rheological characteristics suggests the implication of nanofluids with surfactant to enhance the insulation performance for transformer applications.

Stage division strategy for gas insulation surface discharge based on multi-physical information

The internal insulation defects in gas insulated equipment leading to partial discharges will affect the insulation performance of the equipment. Among them, surface discharges are a typical type of partial discharge, which often occurs at basin-type insulators. To realize effective discharge detection and discharge degree determination, a refined discharge stage division strategy for gas-insulated creeping discharge based on multi-physical information is investigated in this study. First, an experimental platform for gas-insulated multi-physical signal detection is established, of which high frequency current transformer (HFCT), silicon photomultiplier (SiPM), ultra-high frequency (UHF) and acoustic emission (AE) sensors are applied to measurement the multi-physical energy releases in the process of creeping discharge. Then an artificial surface discharge defect is developed following the actual surface discharge of basin insulator. Subsequently, the relative optical radiation power, electromagnetic radiation power and ultrasonic radiation power produced in the process of discharge are deduced from the multi-physical information. Meanwhile, the relationships among the three energy releases are carried out for variation of different energy with the applied voltage increases. Finally, development path of multi-physical energy ratio for surface discharge is proposed to evaluate the severity of discharge.

Comparison between the PD Characteristics of g3 and Dry Air for Gas-Insulated Switchgears

This paper presents a comparison between the partial discharge (PD) characteristics of g3 and dry air for gas-insulated switchgears. PD signals were measured with a conventional method according to IEC 60270 and an ultra-high frequency (UHF) method. The partial discharge inception voltages (PDIVs) of g3 and dry air are about 74% to 84% and 58% to 72%, respectively, in the protrusion on conductor (POC) system, and 90% to 96% and 80% to 93%, respectively, in the free moving particle (FMP) system, depending on the gas pressure of 0.1 MPa to 0.5 MPa. The single PD pulse in time and frequency domains are not distinguished according to gas type. The PRPD patterns have different phase angles depending on the gas type in the POC, while the phase angle is 0–360° in the FMP, regardless of the gas type. Lastly, the correlation was analyzed, showing that the output voltage in mV of the UHF sensor increases linearly in accordance with the apparent discharge in pC, regardless of the gas type. The experimental results in this paper are important as a fundamental database for the application of UHF monitoring systems in an eco-friendly GIS.

Impact of Magnetic Field on Corona Discharge Behavior of Mineral Oil Under AC Voltage

This article reports an experimental investigation of the impact of magnetic field on corona discharge activity in mineral oil, using both ultrahigh-frequency (UHF) and fluorescence techniques under ac voltage. The results show that corona inception voltage (CIV) increased under ac voltage with varying harmonic frequencies without considering any phase shift and reduced marginally under magnetic field. In addition, the impact of the magnetic field shifted the dominating frequency of the UHF signal (0.9 GHz) obtained under ac voltage toward lower frequencies (0.3 and 0.6 GHz). Under high magnetic fields, the parameters such as rise time, fall time, and pulsewidth of the fluorescence signal increased in its magnitude compared to its effect without a magnetic field. Also, using both the UHF sensor and the fluorescence sensor, there was no clear difference in the phase-resolved partial discharge (PRPD) pattern caused by corona discharge (with and without magnetic field). Furthermore, the number of discharges is observed to be high under the impact of harmonic ac voltages with third- and seventh-order containing total harmonic distortions (THDs) of 4% and 40%.

PD Flexible Built-In High-Sensitivity Elliptical Monopole Antenna Sensor.

In view of the insufficient signal detection sensitivity of Gas Insulated Switchgear (GIS), partial discharge (PD), ultra-high frequency (UHF), and failure to conform with GIS surface structure when the existing rigid stereo structure UHF sensor is built in, this paper, using rectangular patch antenna equivalent technique, trapezoidal ground plane technique, and coplanar waveguide (CPW) feed line index asymptotic linearization technique, conducts research on a flexible built-in high-sensitivity elliptic monopole antenna. The flexible antenna, with a thickness of only 0.28 mm, can be kept at a voltage standing wave ratio (VSWR) of less than three in the 300 MHz to 3 GHz band under the curvature radius of 0, 100, 300, and 500 mm, and at less than two in the 650 MHz to 3 GHz band. Through the true 220 kV-GIS partial discharge experimental platform built to analyze the high frequency electromagnetic wave detection performance of the built-in flexible antenna, it is shown that the flexible built-in high-sensitivity elliptical monopole antenna designed in this paper can effectively detect the characteristic signals of high-frequency electromagnetic waves emitted by partial discharges with an average discharge amount below 10 pC.

Study of Ultra High Frequency Measurement Techniques for Online Monitoring of Partial Discharges in High Voltage Systems

Partial Discharge (PD) activity is a pre-cursor for insulation degradation which may eventually lead to catastrophic failure of the electrical equipment with severe social and economic consequences. It is therefore imperative that PD is detected at its early stages to permit repair or replacement, prior to total failure. The bulky non-planar construction of existing ultra-high frequency (UHF) sensors coupled with the lack of proper feeding techniques and the ultrawide signal bandwidth of PD signals which necessitates the use of digital storage oscilloscope have restricted field deployment of UHF technique for online PD detection. In this work, we present a compact ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.58 \boldsymbol {\lambda } $ </tex-math></inline-formula> ) wideband (0.5-3 GHz) dual arm Archimedean slot spiral with coplanar waveguide feed for PD detection, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {\lambda } $ </tex-math></inline-formula> is the wavelength at center frequency. Numerical simulations of the antenna were compared with the measurements of the fabricated antenna. The fabricated wideband antenna was used to detect PD emissions from a mineral oil test cell connected to 10 kVA 50 Hz transformer. We also present different UHF signal measurement techniques ranging from PD pulse detection to reconstruction of the bandlimited PD signal in the digital domain for online structural health monitoring of high voltage systems. The proposed UHF PD measurement techniques are low cost compared to the conventional approach and indicate the feasibility of an embedded system for online PD monitoring using the fabricated UHF sensor.

Flexible Planar Monopole Built-in GIS PD Sensor Based on Meandering Technology.

To address the problem of low space utilization of existing rigid Ultra-High Frequency (UHF) sensors for partial discharge (PD) in Gas-Insulated Switchgears (GIS) and the problem of disrupting the electric field distribution inside the GIS. This paper draws on the idea of flexible wearable antennas and introduces planar monopole antennas commonly used in the communication field as GIS PD detection sensors and carried out research on flexible planar monopole sensing technology built into GIS PD. The VSWR of monopole antenna in the UHF low band is optimized by the meandering technique. The size of the designed flexible antenna is 142 mm × 195 mm × 0.28 mm. The simulation and physical test results show that the improved monopole antenna with meandering technology has a VSWR of ≤2 in the frequency bands 570 MHz–830 MHz, 1.38 GHz–1.8 GHz, and 2.2 GHz–2.76 GHz when the bending radius is 0 mm, 200 mm, and 400 mm, respectively. The VSWR in the frequency band 450 MHz–3 GHz is ≤5. A 220 kV GIS PD detection platform was built to test the performance of the designed antenna, and the results showed that the antenna could detect the PD signal after bending deformation with a high Signal Noise Ratio (SNR).

Attenuation Characteristics and Time Delay of PD Electromagnetic Wave Propagation in GIS Systems

Modeling of electromagnetic wave propagation inside a gas-insulated switchgear structure can be helpful for understanding and improving the utilization of partial discharge detection by providing information to help determine more optimal positioning of ultra-high frequency sensors. This paper studies the effect of insulating spacers, L- and T-type structures on electromagnetic wave propagation by simulating the time dependent wave propagation behavior for these arrangements within a gas-insulated switchgear busbar geometry. The attenuation characteristics and time delays produced by spacers, L- and T-type structures for partial discharge electromagnetic wave propagation behavior are presented. Emphasis is placed on comparison of attenuation characteristics and time delay between different observation points along the busbar both before and after the 90° bends formed by L- and T-type structures. Moreover, a comparative analysis of the radial electric field at the gas-insulated switchgear tank and its rate of change with time is also conducted. The paper demonstrates that if the location of the ultra-high frequency sensor is chosen appropriately based on knowledge of the physical structures, the attenuation effects introduced by L- and T-type structures could be reduced.

Design and experimental analysis of UHF sensor spiral antenna for partial discharge detection of distribution network switchgear

The ultra high frequency (UHF) sensor antenna for detecting partial discharge (PD) in distribution network switchgear is studied. Because of the long period of insulation deterioration in the switchgear, more attention is paid to the middle and later stage of insulation deterioration, and the frequency of PD signal that needs to be paid attention to is wider. Among the commonly used UHF antennas, Archimedes spiral antenna has a wider working frequency band and excellent low-frequency working characteristics, Therefore, Archimedes spiral antennas of UHF Sensors with different outer diameters are designed by using ANSYS HFSS. The influence of the outer diameter of Archimedes spiral antenna on the S11 parameters of Archimedes spiral antenna is studied, and the partial discharge signal acquisition experiments are carried out. The results show that the partial discharge characteristic signals collected by Archimedes spiral antenna with different outer diameters are different. This provides a theoretical basis for the design of UHF sensor antenna used in switch cabinet.

Numerical and Experimental Investigations on Influence of Internal Defect Parameters on Partial Discharge Induced UHF Signals in Gas Insulated Switchgear

A detailed study of the influence of internal defect parameters on partial discharge (PD) induced ultrahigh frequency (UHF) signals propagated through an L section of metal encapsulated gas insulated switchgear (GIS) is presented. The study is carried out using PD defect model with varying rise time, defect size, location, and orientation, an ultrawideband UHF internal sensor, and 3 m long L-GIS with dielectric spacers, shorting plates, hand holes and bus bar with disconnector. Presence of higher order modes, multipath propagation, losses, and dispersion inside L-GIS were observed to influence the time and frequency domain characteristics of PD signals induced in the internal UHF sensor with 0.5 to 6.8 GHz operating bandwidth and directional radiation pattern. The rise time of PD signals significantly influenced UHF signal characteristics in time and frequency domains while PD defect size, location and angular orientation primarily affected the signal amplitude. UHF sensor measurements confirmed the complex behavior of PD induced electromagnetic wave propagation inside L-GIS for varying defect parameters in agreement with the simulations. Despite the complex behavior, it is concluded that PD sensing in GIS is possible using ultrawideband internal UHF sensor.

Planar Ultrawideband Circularly Polarized Cosine Slot Archimedean Spiral Antenna for Partial Discharge Detection

Design and experimental verification of an ultrawideband planar circularly polarized ultrahigh frequency (UHF) sensor is presented for detection of partial discharge (PD) activities in high voltage (HV) equipment. The proposed sensor is cavity-backed cosine slot Archimedean spiral (CSAS) antenna with an electromagnetic (EM) transparent radome. The dual-arm slot spiral was meandered as cosine wave for size reduction and optimized for broadband operation with circular polarization (CP) over 0.5-5 GHz. Unidirectional radiation pattern with CP was achieved over 0.5-5 GHz using an optimized cavity loaded with EM absorber. The fabricated UHF CSAS sensor has the widest operating bandwidth of 0.5-5 GHz with circular polarization and the smallest aperture of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.26\lambda {}_{L}$ </tex-math></inline-formula> when compared to the existing UHF PD sensors, where <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda {}_{L}$ </tex-math></inline-formula> is the wavelength at the lowest operating frequency. Time domain incipient discharge signals and phase resolved PD patterns gathered for three commonly occurring defects in test cells mimicking gas insulated switchgear (GIS) indicate better sensitivity and detection capability for the fabricated CSAS UHF sensor than the reference PD sensor. PD signal measurements and comparison with other UHF PD sensors indicate that the proposed UHF CSAS sensor could be used for PD detection in HV equipment.