Partial Discharge Detection System Research Articles

A distributed PD detection method for high voltage cables based on high precision clock synchronization

Partial discharge (PD) is a crucial cause of high voltage (HV) cable failures. Detecting and locating PD efficiently and effectively is paramount for HV cable maintenance. However, the attenuation of the PD signal after long-distance propagation makes it challenging to identify. This paper presents a distributed PD detection method that significantly reduces the propagation distance of PD signals before the sensor captures them. The technique uses the time-of-arrival to locate PD, whose localization accuracy is directly linked to the clock synchronization (CS) accuracy. CS between different sensors is achieved through three times interactions of the CS signal. The linear frequency modulation (LFM) signal is selected as the CS signal, which can generate a significant gain after pulse compression. It ensures that the CS signal can be effectively recognized after the attenuation of long-distance propagation. The paper also introduces a signal discrimination method based on the short-time Fourier transform that eliminates the influence of the LFM signal on PD identification. The cableless CS method makes it easier to set up before the onsite test. A prototype was implemented and tested. The CS accuracy was measured within 4 ns in the laboratory. An onsite test was carried out to evaluate the performance of the distributed PD detection system. A defect was found at a joint location, which was also confirmed by an additional ultrasonic PD test.

Localization for Dual Partial Discharge Sources in Transformer Oil Using Pressure-Balanced Fiber-Optic Ultrasonic Sensor Array.

The power transformer is one of the most crucial pieces of high-voltage equipment in the power system, and its stable operation is crucial to the reliability of power transmission. Partial discharge (PD) is a key factor leading to the degradation and failure of the insulation performance of power transformers. Therefore, online monitoring of partial discharge can not only obtain real-time information on the operating status of the equipment but also effectively predict the remaining service life of the transformer. Meanwhile, accurate localization of partial discharge sources can assist maintenance personnel in developing more precise and efficient maintenance plans, ensuring the stable operation of the power system. Dual partial discharge sources in transformer oil represent a more complex fault type, and piezoelectric transducers installed outside the transformer oil tank often fail to accurately capture such discharge waveforms. Additionally, the sensitivity of the built-in F-P sensors can decrease when installed deep within the oil tank due to the influence of oil pressure on its sensing diaphragm, resulting in an inability to accurately detect dual partial discharge sources in transformer oil. To address the impact of oil pressure on sensor sensitivity and achieve the detection of dual partial discharge sources under high-voltage conditions in transformers, this paper proposes an optical fiber ultrasonic sensor with a pressure-balancing structure. This sensor can adapt to changes in oil pressure environments inside transformers, has strong electromagnetic interference resistance, and can be installed deep within the oil tank to detect dual partial discharge sources. In this study, a dual PD detection system based on this sensor array is developed, employing a cross-positioning algorithm to achieve detection and localization of dual partial discharge sources in transformer oil. When applied to a 35 kV single-phase transformer for dual partial discharge source detection in different regions, the sensor array exhibits good sensitivity under high oil pressure conditions, enabling the detection and localization of dual partial discharge sources in oil and winding interturn without obstruction. For fault regions with obstructions, such as within the oil channel of the transformer winding, the sensor exhibits the capability to detect the discharge waveform stemming from dual partial discharge sources. Overall, the sensor demonstrates good sensitivity and directional clarity, providing effective detection of dual PD sources generated inside transformers.

Localization of Dual Partial Discharge in Transformer Windings Using Fabry–Pérot Optical Fiber Sensor Array

The power transformer is one of the most critical core devices for energy exchange in power systems, and its safe and stable operation is directly related to the reliability of the power grid. Partial discharge is the main cause of insulation degradation and failure of high-voltage electrical equipment. Online monitoring and accurate localization of partial discharge can provide information on the aging of power equipment, which is of great value for improving the safe operation and maintenance of the power grid. Internal dual partial discharge in transformer windings is a more complex type of fault. Since it is located inside the windings, the signal is attenuated and distorted, making it difficult for traditional monitoring methods to capture such partial discharge signal The Fabry–Perot optical fiber sensor is an ultrasonic detection method that can be built into the transformer interior. This sensor has high sensitivity and a small size, enabling flexible placement at different locations inside the transformer for precise partial discharge detection. Especially for the narrow space inside the high and low voltage windings, F–P sensors can form an array, utilizing the array’s directivity to locate the fault points. In this study, an ultrasonic detection system based on the F–P optical fiber sensor array was developed. The system utilizes a directional cross-localization algorithm based on the multiple signal classification (MUSIC) algorithm to accurately locate dual partial discharge sources. This partial discharge detection system was applied to a 35 kV single-phase transformer, enabling the localization of dual partial discharge sources within the high and low voltage windings. Combined with experimental results, this method exhibits high localization accuracy and is particularly suitable for detecting partial discharge phenomena that occur within or between transformer windings.

A partial discharge detection system based on improved STMS fiber UV sensor

The occurrence of partial discharge in high-voltage transmission equipment can lead to insulation breakdown, emphasizing the critical need for early fault detection. Traditional sensors are highly vulnerable to electromagnetic interference, which significantly impacts the accuracy and reliability of the obtained results. This paper presents an all-fiber ultraviolet (UV) sensor based on the STMS structure coated with zinc oxide (ZnO) composite graphene, realizing partial discharge detection based on optical theory. Firstly, using first principles calculation method, we conducted a comparative study on the ultraviolet-sensitive materials ZnO and ZnO composite graphene. The results demonstrate that the composite material exhibits optical response characteristics that are more suitable for partial discharge detection. Subsequently, sensitive materials with different surface morphology were prepared by hydrothermal method. These materials were uniformly coated on the waist cone region of the STMS optical fiber sensing unit using surface functionalization techniques. The UV test results showed that the flower-shaped ZnO composite graphene coated STMS optical fiber sensing has a higher sensitivity of 857.41 pm/nW cm−2, reaching 1.62 times that of rod-shaped sensitive materials. Finally, the test results of the partial discharge environment indicated that the sensor showed a good linear response when the partial discharge voltage was above 21.55 kV. The UV optical fiber sensor demonstrates promising potential for applications in the field of partial discharge detection.

Improved demodulation method for fibre optic sensors applied in transformer partial discharge detection

AbstractThe 2 × 2 couplers, as a demodulation core of the fibre optic sensing system, have been extensively employed in fibre optic sensors for partial discharge (PD) detection of power equipment. However, the unstable demodulation sensitivity and low signal‐to‐noise ratio (SNR) of such a system are still unsatisfactory in engineering. This work uses a distributed feedback fibre laser as the sensor and employs a common asymmetric 2 × 3 coupler instead of a 2 × 2 coupler as the demodulation core to design a PD detection system. Then, we propose a new demodulation method for PD acoustic emission signals based on the Naval Postgraduate School method. On the PD detection platform, the performance of the conventional detection system and the proposed system is compared. The experimental results show that the proposed system has better reliability and can identify the PD signals in all instances. Furthermore, the average SNR of the new demodulation method is 6.11 dB higher than the traditional 2 × 2 coupler system and can be extended to most PD detection systems using fibre optic sensors.

Partial discharge ultrasonic signals pattern recognition in transformer using BSO-SVM based on microfiber coupler sensor

Detection and pattern recognition of different types of partial discharge (PD) signals in transformer are of great significance for the safe and stable operation of transformers. This paper demonstrates the application of microfiber coupler sensor (MFCS) to the pattern recognition of PD ultrasonic signals with an optimized support vector machine (BSO-SVM) algorithm. First, a PD ultrasonic detection system based on MFCS is built, compared with the traditional piezoelectric sensor, the MFCS can be directly implanted in the transformer oil to detect the PD signals, avoiding the attenuation of ultrasonic signals as they propagate to the transformer outer wall. Then, four kinds of PD ultrasonic signals are collected by the PD detection system, and feature extraction is carried out for the time domain and frequency domain characteristics of PD ultrasonic signals. Finally, a BSO-SVM classification algorithm is proposed, which uses the beetle antennae search (BAS) and the particle swarm optimization (PSO) algorithm to jointly optimize the support vector machine (SVM) algorithm. The BSO-SVM classifier is used to classify four kinds of PD signals, the classification accuracy is 93%, and the number of convergence is 5. In addition, the BSO-SVM algorithm is compared with the GA-SVM and PSO-SVM algorithms. The results show that the BSO-SVM algorithm has higher recognition accuracy and faster convergence speed. The research results show that it is feasible to use MFCS combined with BSO-SVM to identify PD patterns of transformers, and it has certain significance for transformer fault diagnosis.

DFB Fiber Laser Based on External Optical Feedback Theory Applied in Long-Distance Power Transformer Partial Discharge Detection

Active fiber optic acoustic emission (AE) sensors cause external optical feedback (EOF) in engineering applications, resulting in performance loss when used for long-distance partial discharge detection in power transformers. This work employs a distributed feedback fiber laser (DFB-FL) as a sensor to construct a partial discharge detection system. Furthermore, two schemes that improve the long-distance detection performance of DFB-FL are proposed by Suppressing EOF (S-EOF) and Introducing EOF (I-EOF). Then, partial discharge tests in an 80 kVA power transformer validate that both schemes can implement long-distance partial discharge detection. Experimental results indicate that the S-EOF system has a significant signal-to-noise ratio, which is 6.01 dB higher than the piezoelectric transducer (PZT). The S-EOF scheme is suitable for long-term online partial discharge monitoring. The I-EOF system has a high sensitivity for partial discharge detection, and its detectable discharge magnitude is lower than 65.8 pC. The I-EOF scheme is applicable for short-term systemic sampling and daily inspections.

Ultra-High SNR Demodulation Method for Optical Fiber Sensors Applied in Power Transformer Partial Discharge Detection

The demodulation method of optical fiber sensors utilized in power transformer partial discharge (PD) detection is insufficient for engineering applications. We design a distributed feedback fiber laser (DFB-FL) PD detection system with an asymmetric 3 × 3 coupler and propose an ultra-high signal-to-noise ratio (SNR) demodulation scheme by eliminating the main factors that affect the traditional method using an asymmetric 3 × 3 coupler. The power transformer PD detection results reveal that the proposed scheme is free from 3 × 3 coupler asymmetry issues, with an average SNR of 38.30 dB, which is much higher than the widely used demodulation method and the piezoelectric transducer sensor. The average SNR of the system is increased by 24.2 dB with the proposed method.

Research on cable partial discharge detection and location system based on optical fibre timing

Partial discharge (PD) is an important index to reflect the running state of cables. According to the characteristics and propagation mechanism of cable partial discharge signal, a cable partial discharge detection and location system based on optical fibre time synchronisation technology and travelling wave double terminal location principle is developed. The system has high detection sensitivity, high reliability, real-time detection, diagnosis and positioning of cable discharge power supply. The experimental results show that the positioning accuracy of the cable partial discharge source can be effectively improved based on the fibre timing and double terminal positioning technology, and the positioning accuracy can reach 1%; the method studied in this paper can meet the requirements of the accurate location of the partial discharge source of the cable, Gil and other equipment.

Research on cable partial discharge detection and location system based on optical fibre timing

Research on cable partial discharge detection and location system based on optical fibre timing

Partial Discharge and Movement Characteristics of Micron-sized Metal Particles on Insulator Surface in Gas-Insulated Switchgear with Long-time AC Stress

During the transport., assembly., installation., and operation of a gas-insulated switchgear (GIS), the introduction of metal particles into the unit is inevitable. The presence of metal particles on the insulator surface is regarded as a critical factor in insulation failures. Thus, a thorough understanding of the characteristics of metal particles on the insulator surface is critical. In this study, a 126-kV GIS experiment platform with a highly sensitive partial discharge (PD) detection system is established. The movement and PD characteristics of micron-sized metal particles on the insulator surface in a 126-kV GIS under long-time alternating current (AC) stress are investigated. The results demonstrate that the PDs triggered by the micron-sized metal particles are weak and sporadic: the apparent charge of most PDs is lower than 1 pC, and the discharge repetition rate can be as low as once per minute. When two metal particles are sufficiently close to each other, they are charged by the PDs between them. This causes the metal particles to move away from each other and tend to be evenly distributed over the entire insulator surface. Some metal particles can move to stay at the triple junction near the grounded enclosure and center conductor or jump to adhere to the surface of center conductor. This study is anticipated to be a beneficial reference for further understanding the movement and PD characteristics of micron-sized metal particles on the GIS insulator surface.

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

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

Resonant Power Frequency Converter and Application in High-Voltage and Partial Discharge Test of a Voltage Transformer

This paper presents application of a resonant power frequency converter for high-voltage (HV) and partial discharge (PD) test of a voltage transformer. The rating voltage, power, and frequency of the system are 70 kVrms, 40 kVA, and 200 Hz, respectively. The testing system utilized the converter feeding to an HV testing transformer connected to a conventional partial discharge detection system. The converter system comprising a rectifier and insulated-gate bipolar (IGBT) switches with the H-bridge configuration was applied as a low-voltage source instead of a conventional motor-generator test set which requires large space and high cost. The requirements of the test according to the standards are quality of the test voltage and the background noise level. The required voltage must have the different voltage (DV) and total harmonic distortion (THDv) in the acceptable values of less than 5%. The DV is defined as the difference of the root mean square and peak voltages in percent. The required background noise level must be lower than 2.5 pC. Simulations and experiments were performed for verification of the developed system performance in comparison with those of the previously developed system based on the pulse width modulation converter. It is found that the developed system can provide the testing voltage with the DV and the THDv of lower than 1% and the background noise level of lower than 1 pC. Considering this achievement of promising performance, the developed system is an attractive choice for the HV and PD testing of voltage transformers in real practice.

Experimental Research on Partial Discharge of High Voltage Direct Current

Under the action of long-term high-voltage DC voltage, the insulation of electrical equipment is inevitably aging, and it is necessary to monitor its insulation status. Since insulation defects of different nature damage electrical equipment to different degrees, the identification of defects is very important. To this end, a DC partial discharge detection system based on AC partial discharge detection equipment was built, focusing on key issues such as the choice of test power supply, the choice of test frequency, and the choice of pressurization methods. The successful completion of the on-site partial discharge test of UHV converter transformers has provided valuable practical experience for the future on-site partial discharge tests of UHV converter transformers, and provided important tests for the establishment of on-site partial discharge test standards for UHV converter transformers. in accordance with.

Simulation comparison of SSE and TDOA methods for UHF direction finding of partial discharge in substation area

Partial discharge (PD) is not only the main cause of insulation fault for power equipment, but also an important sign of insulation defects. Using the PD detection system based on ultra-high frequency (UHF) antenna array, the PD localization can be realized in air-insulation substation. At present, the methods commonly used in PD detection system localization include time difference of arrival (TDOA) method and spatial spectrum estimation (SSE) method. This paper introduced the principles of these two methods, and proposed a simulation system for PD direction finding. Using this system, the direction finding performance of the TDOA method and the SSE method under different signal-to-noise ratio, incident azimuth angle, rising edge time and array element spacing are compared. The conclusion shows that when the SNR is less than 0 dB or the element spacing is less than 0.23 m, the SSE system has better direction finding performance. When the element spacing is greater than 0.23 m, the SSE system will be fuzzy in direction finding. At this time, the TDOA algorithm can achieve higher direction finding accuracy.

An Improved Partial Discharge Detection System Based on UV Pulses Detection.

Partial discharge (PD) usually reflects failures and potential hazards of equipment, so PD detection is important to protect the power system. The most reliable method now is the pulse current method (PCM), but the device of PCM is large and hard to carry. Ultraviolet (UV) pulse detection is another method to detect PD, which has a high precision, strong anti-interference ability, and a long effective distance. However, the existing detection system does not work well when the PD is weak and can hardly reflect the hidden trouble of equipment. This paper introduces an improved PD detection system, based on the UV Pulse Method, which is of high precision and can reflect early discharge. In this study, a corresponding detection device was also built. This device is handheld, non-contact, easy to use, and of high precision.

Disturbed partial discharge detection system based on an improved Φ-OTDR assisted by a wFBG array.

Partial discharge (PD) detection is an effective method for evaluating the insulation status of power cables. In this paper, a disturbed acoustic sensing (DAS) system based on phase-sensitive optical time-domain reflectometry (Φ-OTDR) for online PD detecting is proposed and demonstrated. To detect the ultra-small fiber strain induced by PD, a weak fiber Bragg grating (wFBG) array is introduced into the sensing fiber to increase signal-to-noise ratio (SNR) of the system. Besides, the sensing fiber is packaged with aluminum tape to enhance the sensitivity. Consistent PD signals in a 10 kV cross linked polyethylene (XLPE) power cable with artificial defects have been observed, and characteristics of the signals are analyzed.

Radiometric localisation of partial discharge sources inside Air‐insulated electrical substation

Monitoring partial discharge (PD) activities inside electrical substation using few ultra high frequency (UHF) sensors mounted around the periphery of the substation could be a useful and economical tool. In this work, an experimental study has been conducted in the laboratory and in substations to investigate the localisation ability of the UHF PD detection system. For localisation, one needs to calculate time difference of arrivals (TDOAs) between the UHF waveforms obtained from the multiple sensors mounted around the substation. After that these TDOAs are used for localisation of the PD sources. In this paper a novel joint entropy (JE)-based TDOAs calculation method is proposed and also compared with the existing techniques. For localisation of PD sources, a modified direction of arrival (DOA)-based method for the near field is proposed, as found to be suitable when the sensors are mounted around the substation. Obtained results in TDOA estimation using the proposed JE method is in line with other technique; however, it was found to provide consistent results and is useful in an extreme situation. Modified DOA-based localisation algorithm found to provide improved performance due to the elimination of approximation as required in previously reported far-field-based localisation system for the air-insulated substations.

High Accuracy Insulation Fault Diagnosis Method of Power Equipment Based on Power Maximum Likelihood Estimation

Partial discharge (PD) detection is one of the most effective methods for electrical equipment insulation fault diagnosis. Most existing PD detection methods are based on the processing of PD waveforms. However, the PD waveforms can be severely disturbed by the complex environment noise in substations, which can lead to great drop in detection accuracy. In this paper, we propose a PD detection method based on power maximum likelihood estimation. This method does not rely on the PD waveforms but utilizes a statistical approach of maximum likelihood estimation to analyze the distribution characteristic of PD signals, transferring the traditional method of waveform processing to a new perspective of statistical analysis. Eventually, the direction of arrival of the PD source can be derived. The proposed method has greatly improved the PD detection accuracy, especially in low signal to noise ratio (SNR) conditions. In simulation tests, it shows a better capability of noise immunity with signal SNR in [–5 dB, 5 dB] range. Field tests performed in a 110-kV substation (SNR around 5 dB) showed that the PD detection accuracy can be improved by up to 70% compared to the traditional methods. Our results may further promote the practical application of substation PD detection system.

Research of UHF External Sensor Performance Calibration Test

UHF sensor is one of the most important parts of GIS equipment partial discharge detection system, and its performance directly affects the accuracy of fault diagnosis results. UHF sensor lacks uniform standard, performs equivalent height test and sensitivity test to calibrate its performance, and builds a UHF sensor performance calibration test platform based on GTEM cell for testing. This paper mainly tests the equivalent height of different types of UHF external sensors at different installation angles. With the UHF detection system, the sensitivity test and performance comparison of each sensor are used to select the better sensor.