Detection and analysis of partial discharge using ultra high frequency sensor

A novel partial discharge (PD) detection method for transformers on site adopting its component as ultra-high frequency (UHF) sensor is proposed. The bushing tap, iron core, and high-voltage (HV) winding can be used as internal UHF sensor for UHF PD detection. The experiments are carried out on an 80-kV transformer model to prove the validity of this method. The results show that the proposed method has good detection sensitivity and anti-disturbance performance, and can measure the PD signals without additional sensor. It solves the problem of the lack of available unused valves for internal UHF sensor installation while the external sensor is susceptible to interference. It provides a novel method with application prospects for PD detection of transformers in field.

This paper proposes an optimal placement model of ultra-high frequency (UHF) sensors for accurate location of partial discharge (PD) in gas-insulated switchgear (GIS). The model is based on 0-1 program in consideration of the attenuation influence on the propagation of electromagnetic (EM) waves generated by PD in GIS. the optimal placement plan improves the economy, observability, and accuracy of PD locating. After synchronously acquiring the time of the initial EM waves reaching each UHF sensor, PD occurring time can be obtained. Then, initial locating results can be acquired by using the Euclidean distance measuring method and the extended time difference of arriving (TDOA) location method. With the information of all UHF sensors and the inherent topological structure of GIS, the locating accuracy can be further improved. The method is verified by experiment, showing that the method can avoid the influence of false information and obtain higher locating accuracy by revising initial locating results.

Partial Discharge (PD) activity is a pre-cursor for insulation degradation which may eventually lead to catastrophic failure of power apparatus with severe social and economic consequences. Electromagnetic emissions gathered over ultra-high frequency (UHF) range (0.5 to 3 GHz) during PD events is widely investigated for health monitoring of high voltage (HV) apparatus. However, large bandwidth of PD induced UHF signals requires high speed digitizer and large storage space which have restricted field deployment of UHF technique for online PD detection. In this work, we present UHF based PD pulse detection framework for remote monitoring and logging of faults in dielectric insulation using ThingSpeak<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TM</sup> cloud. PD events captured by a calibrated UHF sensor from HV PD test cell using the proposed online PD detection framework indicated throughput as high as 83.8% compared with reference UHF sensor measurements gathered by a digital storage oscilloscope. PD detection throughput was observed to be limited by the envelope detection threshold.<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</i><sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in</sub> (10 mV) and cumulative propagation delay <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</i><sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">pd</sub> (∼1 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μs</i>) in the architecture implementation. The proposed UHF sensing technique is low cost compared to conventional approaches, detects a wide range of insulation defects, and scalable for smart monitoring of HV assets using Internet of Things (IoT).

Partial discharge (PD) phenomenon in high-voltage (HV) apparatus is a warning symptom of insulation degradation that can eventually lead to equipment breakdown. The ultra-high frequency (UHF) or electromagnetic method has been widely adopted to monitor the insulation condition of HV power equipment such as power transformers. To detect PD occurrence on HV power transformers, the UHF method is preferable due to its high immunity to external interferences such as background noise and electromagnetic interferences from telecommunication. The UHF antennas are used in the UHF method to detect the electromagnetic waves emitted by PD events inside the power transformer tank. Many studies about the design of UHF antennas to detect PD on power transformers have been conducted previously. However, these UHF sensors are still facing noise disturbances especially for on-line partial discharge measurement, in presence of high noise levels. To address interference issues affecting the UHF sensor sensitivity, this paper presents a novel UHF PD sensor called rectangular microstrip patch antenna or simply patch antenna. This type of antenna has a simple structure, low cost for fabrication, and ultra-wideband (UWB) frequency enabling it to detect PD signals in a wide frequency range within the UHF range (300MHz-3GHZ). To design, simulate and optimize the UHF antenna, the HFSS software was used. The FR4-epoxy substrate having a thickness of 1.6mm, and a dielectric constant of 4.4 was used to design and simulate this rectangular patch antenna. The perfect electric conductor (PEC) was used on the rectangular patch, feedline, and ground plane of the designed patch antenna. The proposed antenna has a low reflection coefficient, low VSWR < 2, a wide bandwidth, as suitable gain, and directivity enabling this antenna to be a suitable and promising sensor for PD detection on power transformers.

This paper proposes a new method to locate the partial discharge (PD) sources inside the high-voltage power transformers with ultra-high frequency (UHF) sensors, based on the time difference of arrival (TDOA) database. A TDOA database includes the TDOA information of possible PD sources inside a power transformer, which is established under the construction of the system of the tested power transformer and the high accuracy of the minimum distance between a possible PD source and a UHF sensor. We employ the tangent transmission model of PD signals and the shortest path algorithm to solve the distance problem in case of an obstacle obstructing the transmission of PD signals. In order to verify the feasibility and accuracy of this new TDOA database method, we carry out two experiments. One experiment was conducted with a 110kV power transformer and the other was carried out with a platform for PD of electric power equipment. The experimental research results which are composed of location coordinates, transmission path and TDOA information indicate that the TDOA database method can locate single PD source as well as multiple PD sources simultaneously with the location error less than 0.3m.

In order to ensure the safe operation of the gas insulated switchgear (GIS), on-site impulse withstand voltage test is becoming more and more important. Oscillating impulse voltage (OIV) is very suitable for the test due to its high efficiency. By detecting the partial discharge (PD) when conducting on-site impulse withstand voltage test, the insulation state of GIS can be known overall. The pulse current, ultrasonic, and ultra high frequency (UHF) are the mainly PD detection methods up to now. Among them, the UHF method is the most suitable method to detect the PD under OIV. However, there are electromagnetic interference signals generated by the impulse voltage generator which will influence the UHF detection results during the on-site impulse withstand voltage test. In this paper, the interference signals for the PD detection using UHF methods are analyzed. Based on this, an interference elimination method by using multiple UHF sensors for PD detection under OIV is introduced. This method is tested both in a lab environment and in field. The analyses show the interference signals for the PD detection using UHF methods under OIV is mainly related to the sphere-gap switch of impulse voltage generator. The results of lab experiments and field tests both show that the interference elimination method by using multiple UHF sensors is suitable for the PD detection under oscillating impulse voltage.

This paper presents a novel self-sensing partial discharge (PD) detection method for power transformers that leverages the transformer's iron core as an ultra-high frequency (UHF) sensor. The method aims to address the limitations of traditional PD detection techniques, which either require intrusive internal sensors or are susceptible to external interference. The experiments conducted on a 220kV transformer model with a suspension discharge defect model demonstrate the high detection sensitivity and anti-interference performance of the proposed method. The results show that the iron core can effectively sense PD UHF signals, providing a reliable and practical approach for on-site PD detection in transformers. This PD detection method solves the problem that the internal UHF sensor has security risks while the external sensor is susceptible to interference. It provides a new method for PD detection of transformers in field.

Self-organizing feature map based unsupervised technique for detection of partial discharge sources inside electrical substations

On-line partial discharge (PD) monitoring is widely used to detect stator winding insulation deterioration. The most common type of on-line PD sensor for turbine generators is the 80 pF capacitive coupler installed at the machine terminals which detects the PD in the very high frequency (VHF) range. More recently, ultra high frequency (UHF) antennae have also been used to detect stator winding PD in large turbine generators. Both types of sensors have been installed in 16 turbine generators. This paper discusses the results from near simultaneous measurements from both types of sensors on the same machines. It was expected that the UHF sensors would have stronger discrimination of the electrical disturbances internal to the machine compared to the VHF sensors, but the VHF sensors would be more sensitive to PD. As expected, the VHF sensors were generally more corrupted by electrical disturbances. However, in about half of the machines investigated here, the UHF sensors were significantly more sensitive than the VHF sensors. Many examples of phase-resolved PD patterns that illustrate these findings are presented.

To ensure the effectiveness of ultra-high-frequency (UHF) method on the on-line monitoring and live detecting of partial discharge (PD) for the gas-insulated metal-enclosed switchgear (GIS), this paper proposes a field calibration method for the UHF PD detection sensors in GIS, which is based on the forward propagation coefficient in the microwave network theory. Firstly, on a full-scare test platform of a 252 kV GIS, the forward propagation coefficients between several pairs of UHF sensors were measured, which agreed well with the frequency spectrum characteristics calculated by the pulse injecting method indirectly and those of PD with different defect types. Then, the criterion corresponding to the detection sensitivity of 5 pC for the proposed method was studied, that is the mean value of forward propagation coefficient between 300MHz and 1.5GHz is not less than −75 dB. Finally, the proposed method including the criterion was applied to the field calibration for the sensitivity of the PD online monitoring UHF sensors in an 1100 kV GIS. Through the above research, differentiated arrangement of UHF sensors was suggested for the on-line monitoring and live detecting of PD in GIS.

The ultra-high frequency (UHF)-based partial discharge (PD) detection technology for gas-insulated switchgear (GIS) has achieved large-scale applications due to its high sensitivity and real-time monitoring capabilities. However, long-term service-induced antenna corrosion in UHF sensors may lead to degraded reception characteristics. To ensure the credibility of monitoring data, on-site sensor calibration under ambient noise conditions is required. This study first analyzes the time–frequency domain characteristics of white noise received by UHF sensors in GIS environments. Leveraging the transceiver reciprocity principle of sensors, a noise reconstruction method based on external sensors is proposed to simulate on-site white noise. Subsequently, CST simulation models are established for both standard and degraded sensors, quantifying the impact of factors like antenna corrosion on performance parameters such as echo impedance S11 and voltage standing wave ratio (VSWR). Finally, the two sensor models are coupled into GIS handholes for comparative simulation analysis. Results show that antenna corrosion causes resonant frequency shifts in sensors, reducing PD signal power by 55.27% and increasing noise power by 64.11%. The signal-to-noise ratio (SNR) decreases from −9.70 dB to −15.34 dB, with evident waveform distortion in the double-exponential PD pulses. These conclusions provide theoretical references for on-site UHF sensor calibration in noisy environments.

Common reasons for local failures in power transformers are partial discharges (PD) in the electric insulation. The ultra-high frequency (UHF) PD measurement method gained in importance for transformer diagnosis and monitoring within the last years. Due to its robustness against external noise, it is suitable for both, factory acceptance tests (FAT) and site acceptance tests (SAT). For the application at acceptance tests, it is necessary that the UHF technique is a reliable testing method and also comparable between different UHF measurement systems. Therefore, the UHF sensor's characteristic has to be included in a calibration procedure by using its antenna factor (AF). This contribution implements a custom-built oil-filled Gigahertz-Transversal-Electromagnetic cell (GTEM cell) for the AF evaluation. In the first part, the GTEM cell's design and dimensioning are illustrated and the cell is evaluated in terms of its high frequency behavior. The second part determines the AF of two different UHF sensor types: UHF Drain Valve Sensors and UHF Plate Sensors using the GTEM cell. Additionally, the influences of insertion depths and standardized gate valves on the Drain Valve Sensor's AF are taken into account.

The requirements for the stability of power system operation are becoming increasingly stringent. As a key equipment in the power system, monitoring the operation of switchgear has become increasingly important. In the work monitoring, traditional monitoring techniques can only monitor a single element separately. Therefore, this study proposes an integrated monitoring technology for passive wireless temperature partial discharge in switchgear based on ultra-high frequency technology. This study takes ultra-high frequency to monitor partial discharge in switchgear and introduces surface acoustic waves for temperature monitoring. Ultra-high frequency sensors and acoustic surface sensors are used to collect temperature electrical signals and partial discharge signals. Then, a passive wireless temperature partial discharge integrated monitoring model for switchgear is constructed. The results showed that the proposed method achieved monitoring accuracy of 94.32%, 93.14%, and 92.5% for three types of partial discharge signals. When conducting temperature monitoring, the temperature obtained by the proposed method is not significantly different from the actual monitored temperature value, indicating good stability during temperature monitoring. The above results indicate that the proposed ultra-high frequency combined with surface acoustic waves can achieve high accuracy in passive wireless temperature partial discharge integrated monitoring of switchgear.

Noise has been a major problem in Partial Discharge (PD) measurement, hampering its effectiveness as a means of assessing insulation condition and of diagnosing faults in power plant insulation. The problem has become more evident in recent years as efforts are made to adopt on-line PD-detection for practical plant insulation condition monitoring. The majority of PD detection systems use Ultra High Frequency (UHF), High Frequency Current Transformer (HFCT), Acoustic Emission (AE) sensors or IEC60270 standard electrical contact systems. Despite great advances which have been achieved in hardware instrumentation over the past years, various forms of noise still affect PD measurements, irrespective of the type of measurement system employed. This paper presents the experience which the authors have accumulated in recent years dealing with noise in PD measurement using the four, aforementioned, measurement systems. Following a brief comparison of the requirement for signal analysis of the four PD measurement systems, the paper addresses the source of noise that often appears in practical applications. Denoising techniques such as the traditional digital filters, matched filters, discrete wavelet transforms and the second generation wavelet transforms will then be introduced and contrasted in terms of their distinct features, advantages and disadvantages. The most effective technique will then be proposed for the four PD measurement systems discussed. Real world data will be used to support the conclusions of the paper.

In order to ensure power supply reliability and reduce a variety of power supply failure, we analyze the development status, advantages and disadvantages of partial discharge detection techniques about the various Gas -insulated Metal-enclosed Swith Gear (GIS). We put forward the application of ultra high frequency (UHF) technology for GIS partial discharge online monitoring technology methods to solve the problems of the difference of the pulse current method of anti-interference ability and ultrasonic sensitivity the problem of low. According to the deficiency of the traditional ultra high frequency sensor, we developed a new window type of ultra high frequency sensor, and compared with conventional in vitro type UHF sensor. Experimental results show that that the window-type UHF sensor sensitivity and anti-jamming capability are superior to conventional high-frequency sensor