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Electronics
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Advanced Online Monitoring and Fault Diagnosis of Power Equipment
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Advanced Online Monitoring and Fault Diagnosis of Power Equipment

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: 28 February 2026 | Viewed by 9542

Special Issue Editors

Dr. Yikai Wang

E-Mail Website
Guest Editor
Department of Electrical Engineering, North China Electric Power University, Baoding 071000, China
Interests: power system protection and control; new power system security risk prevention
Special Issues, Collections and Topics in MDPI journals
Dr. Jiayi Guo

E-Mail Website
Guest Editor
Department of Electrical Engineering, North China Electric Power University, Baoding 071000, China
Interests: vibration and noise analysis of power equipment
Dr. Chenhui Song

E-Mail Website
Guest Editor
School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China
Interests: multi-energy system modeling and security analysis; distribution network security analysis, planning, and operation; new energy development planning
Special Issues, Collections and Topics in MDPI journals
Dr. Junjie Hou

E-Mail Website
Guest Editor
School of Electrical Engineering, Xinjiang University, Urumqi 830000, China
Interests: power system protection and control

Special Issue Information

Dear Colleagues,

Power equipment is the fundamental component of the power system. Its reliability and stability can guarantee the safe and efficient operation of the system. With the development of the power system, the voltage level continues to rise. High-frequency and high-intensity voltage shocks affect the operational reliability of the power equipment. Moreover, the proportion of new energy sources connected to the grid has significantly increased. Since they are connected to the grid through electronic power equipment, the complexity of harmonic components in the power system is exacerbated. Thus, problems with insulation aging and equipment overheating are accelerating, and the lifespan of equipment is shortening. The above issues pose serious challenges to the safety of power equipment. However, traditional equipment monitoring and fault diagnosis methods are difficult to use in order to cope with unexpected situations and have high operational risks and maintenance costs, low diagnostic accuracy, and a lack of generalizability for equipment with different parameters. Therefore, there is an urgent need for advanced online monitoring and fault diagnosis methods for power equipment to achieve real-time comprehensive status monitoring and accurate fault diagnosis.

Dr. Yikai Wang
Dr. Jiayi Guo
Dr. Chenhui Song
Dr. Junjie Hou
Guest Editors

Manuscript Submission Information

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Keywords

  • power equipment protection
  • online monitoring
  • application of artificial intelligence in fault diagnosis
  • mechanical faults
  • partial discharge
  • insulation deterioration
  • fiber optic sensing
  • on-load tap changer
  • multi-parameter fusion

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Published Papers (11 papers)

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Research

27 pages, 8499 KB  
Article
Permanent Fault Identification Scheme for Transmission Lines Based on Amplitude Difference for LCC Injection Signal
by Qi Zhao, Jun Chen, Jie Zhou, Shuobo Zhang, Jinlong Tan and Lu Zhang
Electronics 2025, 14(17), 3526; https://doi.org/10.3390/electronics14173526 - 4 Sep 2025
Viewed by 515
Abstract
A permanent fault identification scheme based on LCC signal injection for high-voltage direct current (HVDC) systems is proposed to avoid secondary damage when it recloses to a permanent fault. Firstly, using the fault control ability of LCC, the additional control strategy is applied [...] Read more.
A permanent fault identification scheme based on LCC signal injection for high-voltage direct current (HVDC) systems is proposed to avoid secondary damage when it recloses to a permanent fault. Firstly, using the fault control ability of LCC, the additional control strategy is applied to the trigger angle of LCC to realize signal injection. The frequency, duration, and amplitude of the injection signal are analyzed and determined, and a signal injection strategy based on LCC is proposed. Secondly, the differences in voltage after signal injection under different fault properties are analyzed under the distributed parameter model. There is a significant difference in the amplitude of the measured voltage at the local end and the calculated voltage at the remote end under different fault properties due to differences in line models. Finally, a normalized area differential is constructed based on the above amplitude difference to realize permanent fault identification. PSCAD/EMTDC simulation results show that the proposed scheme utilizes single end data and is not affected by data communication. There is no need to set a threshold through simulation, and it can reliably identify permanent faults under 400 Ω fault resistance and 40 dB noise. It is suitable for line lengths of 1500 km and below. Full article
(This article belongs to the Special Issue Advanced Online Monitoring and Fault Diagnosis of Power Equipment)
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15 pages, 1432 KB  
Article
Failure Detection with IWO-Based ANN Algorithm Initialized Using Fractal Origin Weights
by Fatma Akalın
Electronics 2025, 14(17), 3403; https://doi.org/10.3390/electronics14173403 - 27 Aug 2025
Viewed by 367
Abstract
Due to the increasing complexity of industrial systems, fault detection hinders the continuity of productivity. Also, many methods in industrial systems whose complexity increases over time have a mechanism based on human intervention. Therefore, the development of intelligent systems in fault detection is [...] Read more.
Due to the increasing complexity of industrial systems, fault detection hinders the continuity of productivity. Also, many methods in industrial systems whose complexity increases over time have a mechanism based on human intervention. Therefore, the development of intelligent systems in fault detection is critical.. Avoiding false alarms in detecting real faults is one of the goals of these systems. Modern technology has the potential to improve strategies for detecting faults related to machine components. In this study, a hybrid approach was applied on two different datasets for fault detection. First, in this hybrid approach, data is given as input to the artificial neural network. Then, predictions are obtained as a result of training using the ANN mechanism with the feed forward process. In the next step, the error value calculated between the actual values and the estimated values is transmitted to the feedback layers. IWO (Invasive Weed Optimization) optimization algorithm is used to calculate the weight values in this hybrid structure. However the IWO optimization algorithm is designed to be initialized with fractal-based weighting. By this process sequence, it is planned to increase the global search power without getting stuck in local minima. Additionally, fractal-based initialization is an important part of the optimization process as it keeps the overall success and stability within a certain framework. Finally, a testing process is carried out on two separate datasets supplied by the Kaggle platform to prove the model’s success in failure detection. Test results exceed 98%. This success indicates that it is a successful model with high generalization ability. Full article
(This article belongs to the Special Issue Advanced Online Monitoring and Fault Diagnosis of Power Equipment)
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29 pages, 3625 KB  
Article
Wind Farm Collector Line Fault Diagnosis and Location System Based on CNN-LSTM and ICEEMDAN-PE Combined with Wavelet Denoising
by Huida Duan, Song Bai, Zhipeng Gao and Ying Zhao
Electronics 2025, 14(17), 3347; https://doi.org/10.3390/electronics14173347 - 22 Aug 2025
Viewed by 435
Abstract
To enhance the accuracy and precision of fault diagnosis and location for the collector lines in wind farms under complex operating conditions, an intelligent combined method based on CNN-LSTM and ICEEMDAN-PE-improved wavelet threshold denoising is proposed. A wind power plant model is established [...] Read more.
To enhance the accuracy and precision of fault diagnosis and location for the collector lines in wind farms under complex operating conditions, an intelligent combined method based on CNN-LSTM and ICEEMDAN-PE-improved wavelet threshold denoising is proposed. A wind power plant model is established using the PSCADV46/EMTDC software. In response to the issue of indistinct fault current signal characteristics under complex fault conditions, a hybrid fault diagnosis model is constructed using CNN-LSTM. The convolutional neural network is utilized to extract the local time-frequency features of the current signals, while the long short-term memory network is employed to capture the dynamic time series patterns of faults. Combined with the improved phase-mode transformation, various types of faults are intelligently classified, effectively resolving the problem of fault feature extraction and achieving a fault diagnosis accuracy rate of 96.5%. To resolve the problem of small fault current amplitudes, low fault traveling wave amplitudes, and difficulty in accurate location due to noise interference in actual wind farms with high-resistance grounding faults, a combined denoising algorithm based on ICEEMDAN-PE-improved wavelet threshold is proposed. This algorithm, through the collaborative optimization of modal decomposition and entropy threshold, significantly improves the signal-to-noise ratio and reduces the root mean square error under simulated conditions with injected Gaussian white noise, stabilizing the fault location error within 0.5%. Extensive simulation results demonstrate that the fault diagnosis and location method proposed in this paper can effectively meet engineering requirements and provide reliable technical support for the intelligent operation and maintenance system of a wind farm. Full article
(This article belongs to the Special Issue Advanced Online Monitoring and Fault Diagnosis of Power Equipment)
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25 pages, 3362 KB  
Article
A Fault Direction Discrimination Method for a Two-Terminal Weakly Fed AC System Using the Time-Domain Fault Model for the Difference Discrimination of Composite Electrical Quantities
by Lie Li, Yu Sun, Yifan Zhao, Xiaoqian Zhu, Ping Xiong, Wentao Yang and Junjie Hou
Electronics 2025, 14(13), 2556; https://doi.org/10.3390/electronics14132556 - 24 Jun 2025
Viewed by 300
Abstract
The project of the flexible direct transmission of renewable energy has become an inevitable development trend for the large-scale grid connection of renewable energy. Its two-terminal weakly fed AC system is often composed of 100% power electronic equipment, which leads to an essential [...] Read more.
The project of the flexible direct transmission of renewable energy has become an inevitable development trend for the large-scale grid connection of renewable energy. Its two-terminal weakly fed AC system is often composed of 100% power electronic equipment, which leads to an essential transformation in fault characteristics and protection requirements. At present, in research, the traditional directional elements are limited by the negative-sequence control strategy, resulting in the decline of their sensitivity and reliability. Therefore, this paper proposes a model for identifying directional elements using composite electrical quantities that is not affected by the control strategy of the two-terminal weakly fed AC system and can reliably identify the fault direction. Firstly, the adaptability of traditional directional elements under the negative-sequence current suppression strategy on both sides of the system when faults occur in the AC line was analyzed. Secondly, based on the idea of model recognition, the model relationship of fault voltage and current in the case of ground faults and non-ground faults occurring at different locations was analyzed. Finally, a fitted voltage was constructed and the Kendall correlation coefficient was introduced to achieve fault direction discrimination. Simulation results demonstrate that the proposed pilot protection scheme can operate reliably under conditions of 300 Ω transition resistance and 25 dB noise interference. Full article
(This article belongs to the Special Issue Advanced Online Monitoring and Fault Diagnosis of Power Equipment)
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23 pages, 6496 KB  
Article
Research on Accurate Fault Location of Multi-Terminal DC Distribution Network
by Zhuolin Chen and Qing Liu
Electronics 2025, 14(10), 1910; https://doi.org/10.3390/electronics14101910 - 8 May 2025
Viewed by 441
Abstract
The rise of direct current (DC) distribution networks, driven by distributed energy storage and large-scale photovoltaic integration, has significantly altered distribution network configurations. In DC networks, short-circuit faults cause a sharp drop in voltage and a rapid increase in current, negatively impacting system [...] Read more.
The rise of direct current (DC) distribution networks, driven by distributed energy storage and large-scale photovoltaic integration, has significantly altered distribution network configurations. In DC networks, short-circuit faults cause a sharp drop in voltage and a rapid increase in current, negatively impacting system stability. To solve this problem, we used an improved red fox optimization (IRFO) algorithm to calculate the distance to failure of the protection device. The algorithm shows higher convergence and accuracy compared to conventional methods. The isolated forest algorithm rejects anomalous data, while an adjustable feedback factor and genetic crossover operator further improve performance. Adaptive interpolation is employed to address low sampling frequency issues, enhancing fault localization precision. Simulations performed in Simulink show that the method is highly resistant to interference with minimal localization error. It is also resistant to changes in system parameters, highlighting its robustness and usefulness in fault localization. Full article
(This article belongs to the Special Issue Advanced Online Monitoring and Fault Diagnosis of Power Equipment)
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24 pages, 4942 KB  
Article
Identification and Localization Study of Grounding System Defects in Cross-Bonded Cables
by Qiying Zhang, Kunsheng Li, Lian Chen, Jian Luo and Zhongyong Zhao
Electronics 2025, 14(3), 622; https://doi.org/10.3390/electronics14030622 - 5 Feb 2025
Viewed by 802
Abstract
Cross-bonded cables improve transmission efficiency by optimizing the grounding method. However, due to the complexity of their grounding system, they are prone to multiple types of defects, making defect state identification more challenging. Additionally, accurately locating sheath damage defects becomes more difficult in [...] Read more.
Cross-bonded cables improve transmission efficiency by optimizing the grounding method. However, due to the complexity of their grounding system, they are prone to multiple types of defects, making defect state identification more challenging. Additionally, accurately locating sheath damage defects becomes more difficult in cases of high transition resistance. To address these issues, this paper constructs a distributed parameter circuit model for cross-bonded cables and proposes a particle swarm optimization support vector machine (PSO-SVM) defect classification model based on the sheath voltage and current phase angle and amplitude characteristics. This model effectively classifies 25 types of grounding system states. Furthermore, for two types of defects—open joints and sheath damage short circuits—this paper proposes an accurate segment-based location method based on fault impedance characteristics, using zero-crossing problems to achieve efficient localization. The results show that the distributed parameter circuit model for cross-bonded cables is feasible for simulating electrical quantities, as confirmed by both simulation and real-world applications. The defect classification model achieves an accuracy of over 97%. Under low transition resistance, the defect localization accuracy exceeds 95.4%, and the localization performance is significantly improved under high transition resistance. Additionally, the defect localization method is more sensitive to variations in cable segment length and grounding resistance impedance but less affected by fluctuations in core voltage and current. Full article
(This article belongs to the Special Issue Advanced Online Monitoring and Fault Diagnosis of Power Equipment)
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13 pages, 2006 KB  
Article
Load Rejection Overvoltage Suppression and Parameter Design Method of UHV AC Transmission Line
by Guanqun Sun, Wang Ma, Yingge Wang, Dian Xu, Haiguang Liu, Rusi Chen and Yixing Ding
Electronics 2025, 14(3), 619; https://doi.org/10.3390/electronics14030619 - 5 Feb 2025
Viewed by 1395
Abstract
UHV (ultra-high voltage) by instant AC transmission system is accompanied by huge reactive power transmission. When the load drops sharply, it is easy to produce serious power frequency overvoltage, which is also defined as load rejection overvoltage. This paper makes an in-depth analysis [...] Read more.
UHV (ultra-high voltage) by instant AC transmission system is accompanied by huge reactive power transmission. When the load drops sharply, it is easy to produce serious power frequency overvoltage, which is also defined as load rejection overvoltage. This paper makes an in-depth analysis from the perspective of voltage increase caused by instantaneous load unloading, and obtains the causes and key influencing factors of load rejection overvoltage. Taking the UHV AC transmission line of a practical project as an example, the suppression effect of the suppression strategy represented by the installation of opening resistance and shunt reactor on the load rejection overvoltage is analyzed. The simulation results show that the above method has an obvious inhibitory effect on load rejection overvoltage. Based on the optimal suppression principle, the optional interval range of the opening resistance and shunt reactor parameters are designed. Full article
(This article belongs to the Special Issue Advanced Online Monitoring and Fault Diagnosis of Power Equipment)
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11 pages, 559 KB  
Article
Fault Diagnosis of Gas Insulated Switchgear Isolation Switch Based on Improved Support Vector Data Description Method
by Nan Zhang, Tianchi Wu, Yunpeng Zhang, Bo Yin, Xuebin Yang, Chengliang Liu and Senxiang Lu
Electronics 2025, 14(3), 540; https://doi.org/10.3390/electronics14030540 - 29 Jan 2025
Viewed by 1009
Abstract
To improve the efficiency and precision of fault diagnosis for isolation switches within Gas-insulated switchgear (GIS), this study introduces an advanced technique utilizing an enhanced support vector data description (SVDD) algorithm. Initially, various operational states of the GIS isolation switch are simulated, and [...] Read more.
To improve the efficiency and precision of fault diagnosis for isolation switches within Gas-insulated switchgear (GIS), this study introduces an advanced technique utilizing an enhanced support vector data description (SVDD) algorithm. Initially, various operational states of the GIS isolation switch are simulated, and the corresponding vibration signals are captured. Subsequently, both the entropy and time-domain features of these signals are extracted to construct a multi-dimensional feature space. High-dimensional feature datasets are then reduced in dimensionality using the kernel principal component analysis (KPCA) method. Furthermore, the conventional SVDD algorithm is modified by incorporating a penalty factor, which allows for a more adaptable classification boundary. This adaptation not only focuses on positive samples but also considers the influence of selected negative samples on the classification hypersphere. Finally, the collected experimental data are classified and predicted. The results indicate that this GIS fault-diagnosis approach effectively overcomes the limitations of traditional methods, which are heavily dependent on training sample data and demonstrate poor algorithm generalization performance. This method is proven to be applicable for the fault diagnosis of isolation switches in GIS. Full article
(This article belongs to the Special Issue Advanced Online Monitoring and Fault Diagnosis of Power Equipment)
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24 pages, 8579 KB  
Article
Research on Directional Elements of Two-Terminal Weak-Feed AC Systems with a Negative Sequence Control Strategy
by Yan Li, Wentao Yang, Xiaofang Wu, Runbin Cao, Weihuang Huang, Faxi Peng and Junjie Hou
Electronics 2024, 13(23), 4647; https://doi.org/10.3390/electronics13234647 - 25 Nov 2024
Viewed by 859
Abstract
It has become a typical scenario in power systems that renewable energy power supply is connected to an AC system through flexible DC transmission. However, since both sides of the AC line are power electronic converters, the negative sequence suppression strategy will be [...] Read more.
It has become a typical scenario in power systems that renewable energy power supply is connected to an AC system through flexible DC transmission. However, since both sides of the AC line are power electronic converters, the negative sequence suppression strategy will be put into the converters at both ends during the asymmetric fault, which causes fundamental changes in the fault characteristics of the system, which is reflected in the two-terminal weak-feed characteristics, leading to the decline of traditional protection performance and affecting the safe operation of the system. Therefore, this paper presents a directional element of a double-ended weakly fed AC system with a negative sequence control strategy. Firstly, the characteristics of the negative sequence impedance under the negative sequence suppression strategy are analyzed when the AC line has asymmetric faults. Secondly, the difference in negative sequence impedance amplitude is analyzed. Finally, the direction element is constructed by the method of de-wave trend analysis The proposed scheme can realize the rapid identification of fault directions at both ends. The simulation results show that the proposed scheme is suitable for a two-terminal weak-feed AC system and can operate reliably under 300 Ω transition resistance and 20 dB noise interference. Full article
(This article belongs to the Special Issue Advanced Online Monitoring and Fault Diagnosis of Power Equipment)
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15 pages, 2439 KB  
Article
Research on the Technology of Improving the Compatibility of DC Measurement Devices Based on the Operation Experience of Siemens Hardware Solutions
by Hao Li, Zicong Zhang, Binghou Ding, Yaoxing Bai, Yong Zheng, Chao Liu and Xincui Tian
Electronics 2024, 13(21), 4194; https://doi.org/10.3390/electronics13214194 - 25 Oct 2024
Viewed by 1018
Abstract
The aim of this study was to manufacture alternative Siemens DC measurement system equipment to solve the problems of increased failure rates of foreign DC measurement equipment and the stopped production of key parts. In this paper, the overall structure and common faults [...] Read more.
The aim of this study was to manufacture alternative Siemens DC measurement system equipment to solve the problems of increased failure rates of foreign DC measurement equipment and the stopped production of key parts. In this paper, the overall structure and common faults of the Siemens DC measurement system are introduced, the difference between TDM signal frame structure and FT3 frame structure is detailed, and the related functional structure, chip type, and function of the Siemens distal module and merging unit (including laser function) are studied. The remote module, merging unit (including laser function), and related hardware design and software design to replace the Siemens DC measurement system were developed, and the test environment and control protection, fault recording wave for communication, and other functional tests were built. The test results show that the domestic remote module, merging unit (laser function), and other technologies communicate normally with the existing Siemens and the domestic mainstream manufacturers, and the accuracy meets the requirements of the 0.2 level. Full article
(This article belongs to the Special Issue Advanced Online Monitoring and Fault Diagnosis of Power Equipment)
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21 pages, 5459 KB  
Article
Fault Localization in Multi-Terminal DC Distribution Networks Based on PSO Algorithm
by Mingyuan Wang and Yan Xu
Electronics 2024, 13(17), 3420; https://doi.org/10.3390/electronics13173420 - 28 Aug 2024
Cited by 2 | Viewed by 1223
Abstract
Flexible DC power grids are widely recognized as an important component of building smart grids. Compared with traditional AC power grids, flexible DC power grids have strong technical advantages in islanding power supplies, distributed power supplies, regional power supplies, and AC system interconnection. [...] Read more.
Flexible DC power grids are widely recognized as an important component of building smart grids. Compared with traditional AC power grids, flexible DC power grids have strong technical advantages in islanding power supplies, distributed power supplies, regional power supplies, and AC system interconnection. In multi-terminal flexible DC power grids containing renewable energy sources such as solar and wind power, due to the instability and intermittency of renewable energy, it is usually necessary to add energy storage units to pre-regulate the power of the multi-terminal flexible DC power grid in islanded operation. Aiming at the important problem of large current impact and serious consequences when the flexible DC distribution network fails, a combined location method combining an improved impedance method (series current-limiting reactors at both ends of the line to obtain a more accurate current differential value) and a particle swarm optimization algorithm is proposed. Initially, by establishing the enhanced impedance model, the differential variables under the conditions of inter-electrode short-circuit and single-pole grounding fault can be obtained. Then tailor-made fitness functions are designed for these two models to optimize parameter identification. Subsequently, the iterative parameters of the particle swarm optimization algorithm are fine-tuned, giving it dynamic sociality and self-learning ability in the iterative process, which significantly improves the convergence speed and successfully avoids local optimization. Finally, various fault types in a six-terminal DC distribution network are simulated and analyzed by MATLAB, and the results show that this method has good accuracy and robustness. This research provides strong theoretical and methodological support for improving the safety and reliability of DC distribution systems. Full article
(This article belongs to the Special Issue Advanced Online Monitoring and Fault Diagnosis of Power Equipment)
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