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Electronics
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Advances in Fault Detection/Diagnosis of Electrical Power Devices
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Advances in Fault Detection/Diagnosis of Electrical Power Devices

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

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 11570

Special Issue Editors

Dr. Hamed Habibi

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Guest Editor
Faculty of Science and Engineering, School of Civil and Mechanical Engineering, Curtin University, Perth, Australia
Interests: control theory; system modelling; advanced control theory; system dynamics modelling; robustness fault diagnosis; nonlinear control; control clean energy; fault detection; fault-tolerant control
Special Issues, Collections and Topics in MDPI journals
Dr. Afef Fekih

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Guest Editor
Department of Electrical and Computer Engineering, the University of Louisiana at Lafayette, Lafayette, LA 70504, USA
Interests: control theory and applications; fault-tolerant control; nonlinear and robust control; dynamic system modelling; applications of the developed control paradigms to complex systems such as aircraft systems; automotive vehicles; power systems; wind turbines and communication systems
Special Issues, Collections and Topics in MDPI journals
Dr. Silvio Simani

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Guest Editor
Department of Engineering, University of Ferrara, Via Saragat 1E., 44122 Ferrara, FE, Italy
Interests: fault diagnosis and fault tolerant control of linear and nonlinear dynamic processes; system modelling; identification and data analysis; linear and nonlinear filtering techniques; fuzzy logic and neural networks for modelling and control; as well as the interaction issues among identification; fault diagnosis; fault tolerant and sustainable control; these techniques have been applied to power plants; renewable energy conversion systems; aircraft and spacecraft processes
Special Issues, Collections and Topics in MDPI journals
Dr. Amirmehdi Yazdani

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Guest Editor
Discipline of Engineering and Energy, College of Science, Health, Engineering and Education, Murdoch University, Perth, WA 6150, Australia
Interests: autonomous systems; intelligent control; optimization; AI in renewable systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Inspired by the need for the improved reliability and efficiency of industrial systems, in the last decade, advanced fault detection and identification schemes have attracted a great deal of attention. This is more crucial and significant for electrical power devices, categorized as cyber-physical systems in the Industry 4.0 framework. This stems from the fact that the behaviors of uncertain electrical systems make the sustainability and efficiency verification of such systems challenging. This becomes even more important in systems categorized as safety-critical, such as electrical power plants in the presence of cyber-attacks. The probability of occurrence of catastrophic faults and failure is increased when there is a high level of uncertainty and variation of the operation point.

On the other hand, with proper and real-time software-based system monitoring, the final cost of the design is considerably decreased, avoiding hardware-based redundancy realization. Additionally, the annual maintenance plan and consequent cost are optimized. This is more impactful for electrical power devices, as they are the parts of any system that are more prone to faults and failure (e.g., the electrical devices in offshore wind turbines).

Reliability-oriented fault detection and fault-tolerant control are state-of-the-art research trends that demand further intensive research in order to obtain applicable cost-effective technology. This motivates the aim of this Special Issue of Electronics. Accordingly, I cordially invite researchers to contribute original and unique articles, as well as review papers. The topics of interest include (with emphasis on electrical power devices), but are not limited to:

  • condition monitoring
  • cyber-attack detection
  • cyber-physical systems
  • data-driven approaches including machine learning methods
  • electrical power devices
  • fault detection and diagnosis
  • fault ride through
  • fault-tolerant control
  • incipient faults
  • observer design
  • signal-based approaches for features extraction

Dr. Hamed Habibi
Prof. Afef Fekih
Prof. Silvio Simani
Dr. Amirmehdi Yazdani
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • condition monitoring
  • cyber-attack detection
  • cyber-physical systems
  • data-driven approaches including machine learning methods
  • electrical power devices
  • fault detection and diagnosis
  • fault ride through
  • fault-tolerant control
  • incipient faults
  • observer design
  • signal-based approaches for features extraction

Published Papers (6 papers)

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Research

22 pages, 5556 KiB  
Article
Ensemble Learning-Enabled Security Anomaly Identification for IoT Cyber–Physical Power Systems
by Hongjun Zhao, Changjun Li, Xin Yin, Xiujun Li, Rui Zhou and Rong Fu
Electronics 2022, 11(23), 4043; https://doi.org/10.3390/electronics11234043 - 05 Dec 2022
Cited by 1 | Viewed by 891
Abstract
The public network access to smart grids has a great impact on the system‘s safe operation. With the rapid increase in Internet of Things (IoT) applications, cyber-attacks caused by multiple sources and flexible loads continue to rise, which results in equipment maloperation and [...] Read more.
The public network access to smart grids has a great impact on the system‘s safe operation. With the rapid increase in Internet of Things (IoT) applications, cyber-attacks caused by multiple sources and flexible loads continue to rise, which results in equipment maloperation and security hazard problems. In this paper, a novel ensemble learning algorithm (ELA)-enabled security anomaly identification technique is proposed. Firstly, the propagation process of typical cyber-attacks was analyzed to illustrate the impact on message transmission and power operation. Then, a feature matching identification method was designed according to the sequence sets under different situations. The classification rate of these abnormal attack behaviors was acquired thereafter, which could aid in the listing of the ranking of the consequences of abnormal attack behaviors. Moreover, the weights of training samples can be further updated according to the performance of weak learning error rates. Through a joint hardware platform, numerical results show that the proposed technique is effective and performs well in terms of situation anomaly identification. Full article
(This article belongs to the Special Issue Advances in Fault Detection/Diagnosis of Electrical Power Devices)
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21 pages, 7462 KiB  
Article
Decreasing the Negative Impact of Time Delays on Electricity Due to Performance Improvement in the Rwanda National Grid
by Darius Muyizere, Lawrence K. Letting and Bernard B. Munyazikwiye
Electronics 2022, 11(19), 3114; https://doi.org/10.3390/electronics11193114 - 29 Sep 2022
Cited by 1 | Viewed by 1132
Abstract
One of the most common power problems today is communication and control delays. This can adversely affect decision interaction in grid security management. This paper focuses on communication signal delays and how to identify and address communication system failure issues in the context [...] Read more.
One of the most common power problems today is communication and control delays. This can adversely affect decision interaction in grid security management. This paper focuses on communication signal delays and how to identify and address communication system failure issues in the context of grid monitoring and control, with emphasis on communication signal delay. An application to solve this problem uses a thyristor switch capacitor (TSC) and a thyristor-controlled reactor (TCR) to improve the power quality of the Rwandan National Grid (RNG) with synchronous and PV generators. It is to counteract the negative effects of time delays. To this end, the TSC and TCR architectures use two methods: the fuzzy logic controller (FLC) method and the modified predictor method (MPM). The experiment was performed using the Simulink MATLAB tool. The power quality of the system was assessed using two indicators: the voltage index and total harmonic distortion. The FLC-based performance was shown to outperform the MPM for temporary or permanent failures if the correct outcome was found. As a result, we are still unsure if TSC and TCR can continue to provide favorable results in the event of a network cyber-attack. Full article
(This article belongs to the Special Issue Advances in Fault Detection/Diagnosis of Electrical Power Devices)
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21 pages, 15097 KiB  
Article
SSA-SL Transformer for Bearing Fault Diagnosis under Noisy Factory Environments
by Seoyeong Lee and Jongpil Jeong
Electronics 2022, 11(9), 1504; https://doi.org/10.3390/electronics11091504 - 07 May 2022
Cited by 2 | Viewed by 2346
Abstract
Among the smart factory studies, we describe defect detection research conducted on bearings, which are elements of mechanical facilities. Bearing research has been consistently conducted in the past; however, most of the research has been limited to using existing artificial intelligence models. In [...] Read more.
Among the smart factory studies, we describe defect detection research conducted on bearings, which are elements of mechanical facilities. Bearing research has been consistently conducted in the past; however, most of the research has been limited to using existing artificial intelligence models. In addition, previous studies assumed the factories situated in the bearing defect research were insufficient. Therefore, a recent research was conducted that applied an artificial intelligence model and the factory environment. The transformer model was selected as state-of-the-art (SOTA) and was also applied to bearing research. Then, an experiment was conducted with Gaussian noise applied to assume a factory situation. The swish-LSTM transformer (Sl transformer) framework was constructed by redesigning the internal structure of the transformer using the swish activation function and long short-term memory (LSTM). Then, the data in noise were removed and reconstructed using the singular spectrum analysis (SSA) preprocessing method. Based on the SSA-Sl transformer framework, an experiment was performed by adding Gaussian noise to the Case Western Reserve University (CWRU) dataset. In the case of no noise, the Sl transformer showed more than 95% performance, and when noise was inserted, the SSA-Sl transformer showed better performance than the comparative artificial intelligence models. Full article
(This article belongs to the Special Issue Advances in Fault Detection/Diagnosis of Electrical Power Devices)
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15 pages, 4732 KiB  
Article
Fault Tolerance Analysis of Five-Level Neutral-Point-Clamped Inverters under Clamping Diode Open-Circuit Failure
by Sajjad Ahmadi, Philippe Poure, Shahrokh Saadate and Davood Arab Khaburi
Electronics 2022, 11(9), 1461; https://doi.org/10.3390/electronics11091461 - 03 May 2022
Cited by 3 | Viewed by 1383
Abstract
Multilevel inverters are increasingly used in industrial applications in which service continuity is crucial. This paper presents an original approach to ensure the fault-tolerant operation of neutral-point-clamped (NPC) inverters in the case of an open-circuit fault event in a clamping diode, which is [...] Read more.
Multilevel inverters are increasingly used in industrial applications in which service continuity is crucial. This paper presents an original approach to ensure the fault-tolerant operation of neutral-point-clamped (NPC) inverters in the case of an open-circuit fault event in a clamping diode, which is rarely investigated in the conducted research work. The proposed fault-tolerant strategy meets the following criteria: restoring rated output voltage and current during post-fault operation, realizing fault-tolerant operation without additional components, maintaining rated total harmonic distortion (THD) during fault-tolerant operation, and fast transition between faulty operation and remedial operation. In the proposed approach, prior to applying the appropriate remedial action, identification of the defective clamping diode is required. In this respect, a very fast and simple logic-based fault diagnosis is presented whose implementation does not need any additional components and external circuit. Moreover, it does not require any component modeling and complicated calculations. The proposed strategy is validated by simulation and experimentation. Full article
(This article belongs to the Special Issue Advances in Fault Detection/Diagnosis of Electrical Power Devices)
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12 pages, 3717 KiB  
Article
A New Detection Method for Load Side Broken Conductor Fault Based on Negative to Positive Current Sequence
by Ali G. Al-Baghdadi, Mohammed Kdair Abd and Firas M. F. Flaih
Electronics 2022, 11(6), 836; https://doi.org/10.3390/electronics11060836 - 08 Mar 2022
Cited by 1 | Viewed by 3190
Abstract
Faults in distribution overhead lines occur due to various reasons, such as rain, strong winds, lightning, and other natural causes. The protection from the load side broken conductor (LSBC) faults has been one of the biggest challenges in the power distribution network. The [...] Read more.
Faults in distribution overhead lines occur due to various reasons, such as rain, strong winds, lightning, and other natural causes. The protection from the load side broken conductor (LSBC) faults has been one of the biggest challenges in the power distribution network. The small current generated by the LSBC fault makes the traditional protection system unable to detect this type of fault. The danger of LSBC fault is still enormous; besides, the available works of literature addressing this issue face difficulties when applying it to the real power system. This paper proposes a new method for detecting LSBC fault using single-ended measurements to the overhead distribution lines. The detection method is based on the constant ratio of negative to positive sequence current measured at the feeder end. The proposed study is performed using MATLAB software to implement a real network as a case study and verified by mathematical analysis. According to obtained results, we demonstrated that the fault in the electrical network had been detected with 100% of feeder protection. The proposed method has the benefit of being applicable and compatible with the existing measurement equipment, even when used in conjunction with overcurrent and earth fault relay in the electrical substation. Therefore, the negative to positive sequence currents are powerful in aiding fault detection. The benefit of this approach is providing a suitable LSBC protection solution for utilities while also opening new prospects in fault detection techniques in the distribution system. Full article
(This article belongs to the Special Issue Advances in Fault Detection/Diagnosis of Electrical Power Devices)
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17 pages, 11330 KiB  
Article
Rapid Detection of Small Faults and Oscillations in Synchronous Generator Systems Using GMDH Neural Networks and High-Gain Observers
by Pooria Ghanooni, Hamed Habibi, Amirmehdi Yazdani, Hai Wang, Somaiyeh MahmoudZadeh and Amin Mahmoudi
Electronics 2021, 10(21), 2637; https://doi.org/10.3390/electronics10212637 - 28 Oct 2021
Cited by 4 | Viewed by 1258
Abstract
This paper presents a robust and efficient fault detection and diagnosis framework for handling small faults and oscillations in synchronous generator (SG) systems. The proposed framework utilizes the Brunovsky form representation of nonlinear systems to mathematically formulate the fault detection problem. A differential [...] Read more.
This paper presents a robust and efficient fault detection and diagnosis framework for handling small faults and oscillations in synchronous generator (SG) systems. The proposed framework utilizes the Brunovsky form representation of nonlinear systems to mathematically formulate the fault detection problem. A differential flatness model of SG systems is provided to meet the conditions of the Brunovsky form representation. A combination of high-gain observer and group method of data handling neural network is employed to estimate the trajectory of the system and to learn/approximate the fault- and uncertainty-associated functions. The fault detection mechanism is developed based on the output residual generation and monitoring so that any unfavorable oscillation and/or fault occurrence can be detected rapidly. Accordingly, an average L1-norm criterion is proposed for rapid decision making in faulty situations. The performance of the proposed framework is investigated for two benchmark scenarios which are actuation fault and fault impact on system dynamics. The simulation results demonstrate the capacity and effectiveness of the proposed solution for rapid fault detection and diagnosis in SG systems in practice, and thus enhancing service maintenance, protection, and life cycle of SGs. Full article
(This article belongs to the Special Issue Advances in Fault Detection/Diagnosis of Electrical Power Devices)
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