Partial Discharge Detection Research Articles

Detection of Partial Discharge in Liquid via Interferometry

Detection of Partial Discharge in Liquid via Interferometry

Partial Discharge Detection Technique Based on Full Convolutional Network with Channel-wise Convolution and Channel Mixing

Abstract The occurrence of partial discharge (PD) serves as an indication of power equipment failure, which, if not given due attention, may result in severe power accidents. Traditionally, the detection of PD involves applying various pre-processing techniques to the original signal and extracting specialized signal features that are subsequently classified using a classifier. The process is intricate and demands extensive expertise. One drawback of the conventional detection approach lies in its failure to consider the information conveyed between the phases of a three-phase electrical signal during the process of identifying PD in medium voltage three-phase cables. The present study proposes a novel method for detecting PDs, which is based on channel-wise convolution and channel mixing(C2CM) using full convolutional networks. Firstly, a set of pulses for each phase of a three-phase signal is extracted and combined to form a three-phase pulse set, serving as the input to the network. Subsequently, we introduce a FCN-C2CM network designed specifically for PD detection, capable of learning both the time-domain features of the input signal and the phase features of the three-phase signal, thereby enhancing recognition accuracy. We evaluated our approach using online testing tools on publicly available datasets, with experimental results demonstrating its superiority over existing.

A Novel Method for Online Diagnostic Analysis of Partial Discharge in Instrument Transformers and Surge Arresters from the Correlation of HFCT and IEC Methods

In this work, a new methodology is proposed for the online and non-invasive extraction of partial discharge (PD) pulses from raw measurement data obtained using a simplified setup. This method enables the creation of sub-windows with optimized size, each containing a single candidate PD pulse. The proposed approach integrates mathematical morphological filtering (MMF) with kurtosis, a first-order Savitzky-Golay smoothing filter, the Otsu method for thresholding, and a specific technique to associate each sub-window with the phase angle of the applied voltage waveform, enabling the construction of phase-resolved PD (PRPD) patterns. The methodology was validated against a commercial PD detection device adhering to the IEC (International Electrotechnical Commission) standard. Experimental results demonstrated that the proposed method, utilizing an off-the-shelf 8-bit resolution data acquisition system and a low-cost high-frequency current transformer (HFCT) sensor, effectively diagnoses and characterizes PD activity in high-voltage equipment, such as surge arresters and instrument transformers, even in noisy environments. It was able to characterize PD activity using only a few cycles of the applied voltage waveform and identify low amplitude PD pulses with low signal-to-noise ratio signals. Other contribution of this work is the diagnosis and fault signature obtained from a real surge arrester (SA) with a nominal voltage of 192 kV, corroborated by destructive disassembly and internal inspection of the tested equipment. This work provides a cost-effective and accurate tool for real-time PD monitoring, which can be embedded in hardware for continuous evaluation of electrical equipment integrity.

The implementation of a cost‐efficient damped AC testing methodology for transmission cables based on DC–AC conversion and distributed partial discharge detection

AbstractThis research introduces a novel damped alternating current (DAC) testing methodology, which integrates an enhanced DAC generator with a pulse‐based distributed partial discharge (PD) detection technique. The advanced DAC generator is designed without the need for high voltage (HV) solid‐state switches, thereby offering a cost‐effective solution for field‐testing voltage generation through a direct current–alternating current conversion approach. To meet the demand for high instantaneous power, a capacitor bank is employed as the power supply. Furthermore, the implementation of a distributed PD detection technique enhances sensitivity and eliminates limitations associated with cable length. To minimize the construction costs of the distributed PD‐detection system, a pulse synchronization technique has been employed. Efforts to reduce the system's weight were informed by simulations, resulting in the design and development of a prototype weighing 850 kg for a 64/110 kV power cable. The reduction in the number of HV solid‐state switches contributes to significant cost savings, amounting to tens of thousands of dollars, when compared to conventional DAC generators. Laboratory and field tests validated the effectiveness of the cost‐efficient DAC testing methodology.

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.

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.

Two-Dimensional Material-Based Fluorescent Optical Fiber for Early Detection of Partial Discharge

Two-Dimensional Material-Based Fluorescent Optical Fiber for Early Detection of Partial Discharge

Partial discharge detection, diagnosis, and location technology based on a novel transient earth voltage-ultrasonic integrated sensor used for switchgear equipment.

Medium-voltage (MV) switchgear and gas insulated switchgear (GIS) are essential components of power-grid systems. Their safe operation is crucial for the electricity consumption of users. However, insulation faults often occur during the operation of MV switchgear and GIS because of pollution, humidity, heat, mechanical shock, and other factors. Partial discharge (PD) measurements are the most effective indicator to prevent insulation failure. Transient earth voltage (TEV) and ultrasonic methods are the most popular PD measurement methods for switchgear. Currently, these two methods are used widely and independently. In this study, a novel TEV-ultrasonic integrated sensor is proposed based on the independent structure of the TEV and the ultrasonic sensor. The performance parameters of the proposed sensor were tested on test platforms. PD measurement experiments were conducted in a 10kV switchgear and 220kV GIS to analyze the performance of the integrated sensor. The results show that the sensor can simultaneously measure the TEV and ultrasonic signals in the same location. The integrated sensor can realize effective and sensitive detection, precise location, and accurate diagnosis of PD in the MV switchgear and GIS.

Novel Antenna for Partial Discharge Detection and Classification: A Convolutional Neural Network-Based Deep Learning Approach

Novel Antenna for Partial Discharge Detection and Classification: A Convolutional Neural Network-Based Deep Learning Approach

Research on Miniaturized and Wideband UHF Sensing Technology for Partial Discharge Detection of Power Equipment Based on Serpentine Bending

Research on Miniaturized and Wideband UHF Sensing Technology for Partial Discharge Detection of Power Equipment Based on Serpentine Bending

An automatic robot for ultrasonic partial discharge detection of gas-insulated switchgear

Purpose Gas-insulated switchgear (GIS) stands as a pivotal component in power systems, susceptible to partial discharge occurrences. Nevertheless, manual inspection proves labor-intensive, exhibits a low defect detection rate. Conventional inspection robots face limitations, unable to perform live line measurements or adapt effectively to diverse environmental conditions. This paper aims to introduce a novel solution: the GIS ultrasonic partial discharge detection robot (GBOT), designed to assume the role of substation personnel in inspection tasks. Design/methodology/approach GBOT is a mobile manipulator system divided into three subsystems: autonomous location and navigation, vision-guided and force-controlled manipulator and data detection and analysis. These subsystems collaborate, incorporating simultaneous localization and mapping, path planning, target recognition and signal processing, admittance control. This paper also introduces a path planning method designed to adapt to the substation environment. In addition, a flexible end effector is designed for full contact between the probe and the device. Findings The robot fulfills the requirements for substation GIS inspections. It can conduct efficient and low-cost path planning with narrow passages in the constructed substation map, realizes a sufficiently stable detection contact and perform high defect detection rate. Practical implications The robot mitigates the labor intensity of grid maintenance personnel, enhances inspection efficiency and safety and advances the intelligence and digitization of power equipment maintenance and monitoring. This research also provides valuable insights for the broader application of mobile manipulators in diverse fields. Originality/value The robot is a mobile manipulator system used in GIS detection, offering a viable alternative to grid personnel for equipment inspections. Comparing with the previous robotic systems, this system can work in live electrical detection, demonstrating robust environmental adaptability and superior efficiency.

Optical signals measurement of discharge plasma in air switch cabinet using a fluorescent optical fiber as the sensor

Air switch cabinets are widely employed in the power industry, there is, however, no reliable methods for detecting partial discharges (PDs). Because fiber optic-based sensors are easy to install and have anti-electromagnetic interference capabilities, they are well suited for PDs detection in switch cabinets with their many components and metal shell structure. In this work, corona discharge in an air switch cabinet was detected using fluorescent fiber, and the characteristics of PDs were analyzed. Furthermore, experimental investigations were conducted to explore the impact of gas pressure and fiber length on the PDs detection. The results exhibit a correlation between the aforementioned factors and the PDs’ total amplitude, maximum amplitude, number of pulses and detection limit of PD quantity. The results can provide references for the application of fluorescent optical fiber on the PD detection in air switch cabinet.

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.

Comparative Study on Multiple Methods for Partial Discharge Detection of Gap Defect in Medium Voltage Switchgear

Abstract The medium voltage switchgear is a key equipment in the distribution network of the power system, which directly faces users. Once a fault occurs, it will cause huge economic losses and adverse social impacts. Partial discharge measurement is an important means to ensure the safe operation of switchgear. The physical quantities measured by different partial discharge detection methods are different, so the detection effects by different methods for the same defect are also different. This paper takes the common internal air gap defects of solid insulation in switchgear as the research object, and conducts partial discharge detection tests on real switchgear equipment. At the same time, radio frequency method, ultrasonic method, transient earth voltage (TEV) method, and pulse current method are used to detect and analyze the partial discharge generated by the defect. The results show that the radio frequency method, TEV method, and pulse current method have good detection sensitivity for air gap defects, but the ultrasonic method cannot detect this type of defect. Comparing the amplitudes of the three electrical signals, it can be found that the correlation between the TEV method and the pulse current method is relatively high, while the correlation between the radio frequency method and the two is relatively low. As the applied voltage increases, the amplitude of the radio frequency method changes linearly, which can more sensitively reflect the degree of defect change.

Luminescent fiber UV detection.

Herein, a luminescent fiber device for detecting ultraviolet (UV) intensity, which comprises a UV probe and a photoelectric converter, is proposed. The UV probe consists of a glass tube filled with luminescent material, which can be used for the efficient radiation conversion of UV radiation to the visible spectral region. The luminescent material, Y2O2S:Eu3+, is mixed with polydimethylsiloxane (PDMS) to form the core of the UV probe. Subsequently, the UV radiation response of the luminescent fiber device is investigated; the experimental results demonstrate that the direction-independent UV detection can be realized by using this luminescent fiber UV detection device while UV light is radiated radially along the UV probe. In addition, since partial discharge (PD) is accompanied by UV radiation, we hope to develop a spectral PD detection scheme based on optical fiber technology, which can broaden the role of optical technology and optical fiber technology in the field of PD detection.

Research and Simulation of Partial Discharge Phenomenon Sensing Technology for Substation Inspection Robots

Abstract This paper thoroughly investigates the phenomenon of partial discharge in substations and proposes a set of simulation experimental apparatus to replicate various types of partial discharge defects in switchgear. By modifying the switchgear, incorporating models for different types of partial discharge, and equipping various standard partial discharge sensors, accurate simulations of phenomena such as point discharge, suspended discharge, gap discharge, and particle discharge are achieved. Through this system, the effectiveness of different detection methods, such as ultrasonic, high-frequency, and transient voltage methods, is validated for various defect models. Furthermore, utilizing an indoor inspection robot guide rail, the paper simulates the environment of partial discharge in substations, enabling the validation of the robot’s partial discharge detection performance and typical patterns under different conditions. This work is dedicated to providing situational awareness technology for partial discharge phenomenon detection for substation inspection robots, so that the inspection robot can detect various abnormal partial discharge phenomena in transformers or other substation equipment through micro sensors to promote the stable operation of the substation.

Analysis and Treatment of a Partial Discharge Fault in a 220kV Transformer

Abstract Partial discharge test of transformer is one of the most important detection items in the factory test of transformer, which is related to whether the transformer can operate safely and stably. This article will analyze a case of partial discharge exceeding the standard in a 220kV transformer. Based on the joint detection technology of ultrasonic partial discharge and ultra high frequency partial discharge, the defect location will be found. And the structure of the transformer will be researched to identify the cause of the defect. The diagnosis and treatment will be successfully completed. Finally, the conclusion will be verified through finite element analysis. This provides reliable guidance for partial discharge detection and rectification measures in transformers’ production and operation.

Novel dual‐resonance damped alternating current testing system for offline partial discharge measurement of power cables

AbstractTo accurately detect the early deterioration of electrical insulation in power cables, an energizing system is required for offline partial discharge (PD) measurements. The damped alternating current (DAC) testing system has emerged as an effective tool for inducing PD events. However, the existing systems often suffer from limitations such as signal interference, low sensitivity, and high costs. To address these issues, this study proposes a novel dual‐resonance DAC testing system that is simple in structure and cost‐effective. The prototype was built for testing 10‐kV distribution cables, and its effectiveness was validated through experimental tests on a cable sample. The results show that this approach significantly improves PD detection sensitivity and successfully completes PD localization. This research contributes to the development of more efficient and affordable DAC generation technology for power cable testing applications.

Hardware and Software Design of Programmable Medium and High-Speed Data Acquisition (DAQ) Board of Fiber Optic Signal for Partial Discharge Acquisition

The anti-electromagnetic interference capability of partial discharge (PD) acoustic signal conversion and collection circuits severely restrict the sensitivity of PD detection. The data acquisition (DAQ) systems available in the current market are costly and have limited functionality, making it difficult to satisfy the acquisition requirements for PD detection. This paper proposes a medium to high-speed fiber optic signal acquisition board with an adjustably controlled sampling rate and filter cutoff frequency. The circuit achieves a higher signal-to-noise (SNR) ratio by distributing the noise in each part of the signal acquisition chain reasonably. The temperature characteristics of the acquisition module are improved by utilizing the programmable T-type structure for transimpedance amplification of photocurrent. The DAQ card performs data acquisition and processing using STM32H743 internal ADC and caches data in bulk with an SRAM and SD card. A data uploading method based on time reference has been proposed, which enables full, effective information signal upload through a low-cost transmission interface. The research ultimately achieves a stable sampling of three channels at 1 MSps, SNR of 63 dB, and programmable gain amplification of the photocurrent with 0–60 dB. Finally, the system is used for PD acoustic signal acquisition in the frequency range of 20 Hz to 100 kHz.

Design of partial discharge detection device based on BP neural network algorithm

Abstract At present, with the rapid development of science and technology, the construction of new power systems has been promoted rapidly, and the automation and intelligence of power network operation equipment has been continuously improved. It is increasingly important to use various detection techniques for the state detection of power grid operating equipment. In this paper, a design scheme of partial discharge detection device based on neural network BP algorithm is achieved, combining with the current detection technology and embedded technology. The purpose of discovering and evaluating the insulation defects of power grid equipment is to detect partial discharge.