Research on Integrated Technology of PD Ultrasonic Signal and UHF Signal Detection

Zhang, Guozhi; Lu, Changyue; Yu, Xingyu; Tian, Hanlv; Zhang, Xiaoxing

doi:10.1109/ichve53725.2022.9961712

Cited by 3 publications

(3 citation statements)

References 4 publications

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“…Therefore, we point out three development directions of UHF PD sensors: a) optimize the antenna design to achieve the characteristics of small size, high gain, and broadband [227]; b) design of flexible or self-sensing UHF sensors to make the sensors conformal with power equipment body [228], [229]; c) design of integrated sensors that can perceive multiple kind of PD excited signals [230].…”

Section: ) New-type Uhf Sensorsmentioning

confidence: 99%

A Comprehensive Review of Signal Processing and Machine Learning Technologies for UHF PD Detection and Diagnosis (II): Pattern Recognition Approaches

Long,

Xie,

Wang

et al. 2024

IEEE Access

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Partial discharge (PD) pattern recognition approaches are designed to identify the types or severities of the insulation defects within the high voltage equipment, which is vital for evaluating potential harmfulness and making follow-up maintenance plan. In recent years, many advanced machine learning (ML) algorithms have been introduced to this field and achieved remarkable results. As the second one of the two-part papers, we aim to give a comprehensive review regarding the pattern recognition approaches for ultra-high frequency (UHF) PD data in this paper. These methods are grouped into three categories, which are the traditional ML-based PD type recognition, the deep learning-based (DL) PD type recognition, and PD severity assessment. Specifically, for the first topic, feature extraction methods, dimensionality reduction methods and classification methods are reviewed separately. For the second topic, many state-of-the-art DL methods are discussed, including the deep belief network (DBN), deep autoencoder network (DAN), convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), graph convolutional network (GCN), deep ensemble learning (DEL), etc. For the third topic, the relevant algorithms are also divided into the conventional ML-based ones and the DL-based ones, which are studied in detail respectively. Finally, a brief discussion about the application effects of the above technologies is given, and some future directions are suggested. This paper covers almost every aspect of the PD pattern recognition and highlights the latest progress, which can provide valuable references for scholars in this field.

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Section: ) New-type Uhf Sensorsmentioning

confidence: 99%

A Comprehensive Review of Signal Processing and Machine Learning Technologies for UHF PD Detection and Diagnosis (II): Pattern Recognition Approaches

Long,

Xie,

Wang

et al. 2024

IEEE Access

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“…At the same time, influenced by the size of the sensor feeder, 39 mm is the minimum size allowed, so the back cavity depth of the sensor is set to 39 mm. By HFSS finite element software simulation optimization [22], the length l of the sensor is set at 74 mm, and the width w is 104 mm (corresponding angle θ is about 110°), and the metal cavity length l 1 , width w 1 and depth h 2 are 91, 127, 39 mm, separately, as shown in Table 1.…”

Section: Sensor Sizementioning

confidence: 99%

External UHF Sensor for GIS PD Insulation Defect from Resin Hole

Li¹,

Xu²,

Zhang³

et al. 2023

Energy Engineering

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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.

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“…Based on studies many researchers have investigated various detection techniques, such as pulse current method, ultrasonic method, ultra high frequency (UHF) method, optical measurement method, etc [24][25]. However, the filters employed in the detection method frequently do not use HPF as the signal's filtering component, and in some instances, they do not use any filters at all.…”

Section: Introductionmentioning

confidence: 99%

Development of Second Order High Frequency Filter for Partial Discharge Measurement

Syed Akhmal Syed Jamalil,

Zalikha Shamsul,

Muzamir Isa

et al. 2024

ARASET

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Partial discharge (PD) can occur on any high-voltage equipment. This study is particularly concerned with the PD that occurs on underground cables. Researchers frequently struggle to isolate interference noise from the PD signal when doing PD measurements. Therefore, to reduce the interference noise during PD measurements, Sallen-Key high-pass filters with a 500 kHz, or a little bit higher cut-off frequency are designed. This filter is designed with a designated cut-off frequency value because the frequency range of the PD signal is between 1 MHz to 1 GHz. Based on the results of experimental testing for actual filters, the designed filter is a high-pass filter with a cut-off frequency of 500KHz. When the generator function's input frequency values are set between 500 kHz and 2.4 MHz, the signal will pass the filter and provide output values for both frequencies and amplitude. However, at frequencies lower than 500 kHz, the signal is beginning to be filtered and the output signal's amplitude is getting close to zero. Based on the PD testing results, there is interference on the PD signal shown on the oscilloscope when a 1kV supply is applied to an underground cable without using a filter. But, when the proposed filter is used in PD testing, the ripple voltage is reduced from 123 mV to 67 mV. This proves that when the designed filter is used in PD testing, it can reduce interference noise on the PD signal.

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Research on Integrated Technology of PD Ultrasonic Signal and UHF Signal Detection

Cited by 3 publications

References 4 publications

A Comprehensive Review of Signal Processing and Machine Learning Technologies for UHF PD Detection and Diagnosis (II): Pattern Recognition Approaches

A Comprehensive Review of Signal Processing and Machine Learning Technologies for UHF PD Detection and Diagnosis (II): Pattern Recognition Approaches

External UHF Sensor for GIS PD Insulation Defect from Resin Hole

Development of Second Order High Frequency Filter for Partial Discharge Measurement

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