A Comprehensive Review of Signal Processing and Machine Learning Technologies for UHF PD Detection and Diagnosis (I): Preprocessing and Localization Approaches

Long, Jiachuan; Wang, Xianpei; Zhou, Wei; Zhang, Jun; Dai, Dangdang; Guang, Zhu

doi:10.1109/access.2021.3077483

Cited by 35 publications

(16 citation statements)

References 117 publications

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“…Energies 2021, 14, x FOR PEER REVIEW 2 of 16 and even destruction of the insulating elements [9][10][11][12][13][14][15][16][17][18][19]. Therefore, it is necessary to control the occurrence of local overvoltage during the high-voltage insulation operation.…”

Section: Methodsmentioning

confidence: 99%

“…Thus, the possibility of contactless detection of sources of electric fields appears important to determine the degree of their influence on the surrounding space. Additionally, the registration of local overvoltage in transformer windings, in high-voltage insulators and cables, can indicate the presence of insulation defects, which ultimately cause damage and even destruction of the insulating elements [9][10][11][12][13][14][15][16][17][18][19]. Therefore, it is necessary to control the occurrence of local overvoltage during the high-voltage insulation operation.…”

Section: Introductionmentioning

confidence: 99%

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Non-Contact Methods for High-Voltage Insulation Equipment Diagnosis during Operation

et al. 2021

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The article describes a complex of non-contact methods for remote diagnosis of high-voltage insulators as well as the two-channel method for remote diagnostics of the operating state of high-voltage insulators, based on the registration of partial discharges by electromagnetic and acoustic sensors. The presented device allows visual inspection and searches for faulty high-voltage equipment and a remote non-contact method of recording high-intensity electric fields of industrial frequency and their spatial distribution based on the electro-optical effect. The scheme of using the system for monitoring and diagnosing the technical condition of high-voltage support insulators of open switchgear is described. The results of experimental studies confirm the possibility of industrial applicability of the proposed method for non-contact remote diagnostics of the state of high-voltage insulators under operating voltage.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Non-Contact Methods for High-Voltage Insulation Equipment Diagnosis during Operation

et al. 2021

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“…The TEV method is the optimal solution in switchgear due to its high sensitivity, uninterrupted power supply, strong anti-interference performance, easy installation, and non-instructive method [ 52 ]. Some examples of various PD localization methods (including data-driven methods using neural networks) are presented and reviewed in [ 53 , 54 ].…”

Section: Applications Of Measurement Data Manipulationmentioning

confidence: 99%

Switchgear Digitalization—Research Path, Status, and Future Work

Kaštelan

Vujović

Krčum

et al. 2022

Sensors

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To keep pace with global energy efficiency trends and, in particular, emission reduction targets in the maritime sector, both onshore and maritime power distribution systems need to be adapted to the relevant new technologies and concepts. As an important link in the distribution chain, medium-voltage switchgear (MV) is expected to be stable and reliable while operating as efficiently as possible. Failures of MV equipment, while rare because the equipment must be safe to handle and use, have far-reaching consequences. The consequences of such failures, whether to the shore or marine power system, present risks to the entire power plant, so an accurate assessment of equipment condition is required to identify potential failures early. The solution is an emerging concept of digital switchgear, where the implementation of sensor technology and communication protocols enables effective condition monitoring, and the creation of a database that, when combined with machine learning algorithms, enables predictive maintenance and/or fault detection. This paper presents, step by step, the previous challenges, the current research (divided into predictive maintenance, condition monitoring, and fault detection categories), and the future directions in this field. The use of artificial intelligence is discussed to eliminate the disadvantage of manually interpreting operational data, and recommendations for future work are formulated, such as the need to standardize test procedures and data sets to train and compare different algorithms before they are used in practice.

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“…Extensive research has been done on the use of traditional machine learning techniques in high voltage applications, e.g., [4][5][6][7]. This paper only considers the literature that employs deep learning techniques.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning in High Voltage Engineering: A Literature Review

et al. 2022

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Condition monitoring of high voltage apparatus is of much importance for the maintenance of electric power systems. Whether it is detecting faults or partial discharges that take place in high voltage equipment, or detecting contamination and degradation of outdoor insulators, deep learning which is a branch of machine learning has been extensively investigated. Instead of using hand-crafted manual features as an input for the traditional machine learning algorithms, deep learning algorithms use raw data as the input where the feature extraction stage is integrated in the learning stage, resulting in a more automated process. This is the main advantage of using deep learning instead of traditional machine learning techniques. This paper presents a review of the recent literature on the application of deep learning techniques in monitoring high voltage apparatus such as GIS, transformers, cables, rotating machines, and outdoor insulators.

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A Comprehensive Review of Signal Processing and Machine Learning Technologies for UHF PD Detection and Diagnosis (I): Preprocessing and Localization Approaches

Cited by 35 publications

References 117 publications

Non-Contact Methods for High-Voltage Insulation Equipment Diagnosis during Operation

Non-Contact Methods for High-Voltage Insulation Equipment Diagnosis during Operation

Switchgear Digitalization—Research Path, Status, and Future Work

Deep Learning in High Voltage Engineering: A Literature Review

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