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Electronics
Special Issues
Real-Time Fault Detection and Diagnosis of Industrial Electronics Equipment
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Real-Time Fault Detection and Diagnosis of Industrial Electronics Equipment

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

Deadline for manuscript submissions: 31 July 2025 | Viewed by 883

Special Issue Editor

Prof. Dr. Wei Wang

E-Mail Website
Guest Editor
School of Electrical Engineering, Southeast University, Nanjing 210096, China
Interests: motor drives; servo control; fault-tolerant control and fault diagnosis of AC machines; electrified transportation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Electric equipment plays a vital role in many areas including industrial production, transportation and energy supply. During long-term operation, electric equipment suffers from many issues including overvoltage, overcurrent, insulation aging and component wear. These issues can cause faults in electric equipment and degrade its performance and efficiency. In some cases, it may even lead to major safety accidents and huge economic losses. Hence, novel advancements in real-time fault detection and diagnosis of electric equipment requires deeper exploration.

In order to achieve precise and reliable fault detection, signal sampling, signal processing analysis and machine learning technologies are applied to algorithm design. In addition, condition monitoring can also be applied for extremely minor faults.

This Special Issue of Electronics, entitled ‘Real-Time Fault Detection and Diagnosis of Industrial Electronics Equipment’, aims to present the latest research on real-time fault detection and diagnosis for electric equipment, providing a platform for researchers from both academic and industrial fields to showcase their theoretical and technological advancements.

Original research articles and reviews are welcome on topics including (but not limited to) the following research areas:

(1) Techniques for real-time fault diagnosis in electric equipment;

(2) Development of real-time condition monitoring techniques;

(3) Integrated research on advanced fault diagnosis algorithms;

(4) Application of machine learning in fault diagnosis;

(5) Fault feature extraction and processing of sensor signals.

We look forward to receiving your contributions. 

Prof. Dr. Wei Wang
Guest Editor

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

  • fault detection and diagnosis
  • condition monitoring
  • diagnostic algorithms integration
  • machine learning
  • signal processing

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Published Papers (2 papers)

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Research

15 pages, 2995 KiB  
Article
Low-Cost Robust Detection Method of Interturn Short-Circuit Fault for Distribution Transformer Based on ΔU-I Locus Characteristic
by Jinwei Lin, Tao Ji, Han Zhu, Yunlong Wang, Jialei Hu, Yonghao Sun and Wei Wang
Electronics 2025, 14(12), 2458; https://doi.org/10.3390/electronics14122458 - 17 Jun 2025
Viewed by 141
Abstract
Winding interturn short-circuit (ISCF) fault is a common problem which occurs in distribution transformers due to multiple internal and external factors. Unfortunately, the variations in electric parameters under a slight fault are tiny and hardly used as effective characteristics for the detection and [...] Read more.
Winding interturn short-circuit (ISCF) fault is a common problem which occurs in distribution transformers due to multiple internal and external factors. Unfortunately, the variations in electric parameters under a slight fault are tiny and hardly used as effective characteristics for the detection and protection system. To address this issue, a low-cost robust detection method of ISCF based on the port voltage–current (ΔU-I) locus characteristic is presented in this paper. The mathematical model of the three-phase distribution transformer with ISCF is first established. Then, the ΔU-I locus function and relevant characteristic parameters are analyzed, respectively, which can reflect the healthy and faulty conditions. The axis length ratio between the major axis length and the minor axis length in the ΔU-I ellipse curve is defined as the fault indicator for the sensitivity and robustness of fault diagnosis. Moreover, this method can reduce the number of sensors and has strong robustness against load fluctuations. In the end, the theoretical analysis and simulation results verify the effectiveness of the ΔU-I locus characteristic. Full article
(This article belongs to the Special Issue Real-Time Fault Detection and Diagnosis of Industrial Electronics Equipment)
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13 pages, 3315 KiB  
Article
Impedance Monitoring of Capacitively Coupled Plasma Based on the Vacuum Variable Capacitor Positions of Impedance Matching Unit
by Hwang Gyu Kim, Jiseok Lee and Sang Jeen Hong
Electronics 2025, 14(10), 2022; https://doi.org/10.3390/electronics14102022 - 15 May 2025
Viewed by 463
Abstract
Plasma impedance monitoring in semiconductor manufacturing processes is performed using external sensors, such as voltage-current (VI) probes or directional couplers. Plasma chamber impedance measurements, conducted in non-50 Ω matched transmission lines, suffer from a lack of clean signals due to phase variations and [...] Read more.
Plasma impedance monitoring in semiconductor manufacturing processes is performed using external sensors, such as voltage-current (VI) probes or directional couplers. Plasma chamber impedance measurements, conducted in non-50 Ω matched transmission lines, suffer from a lack of clean signals due to phase variations and the nonlinearity of plasma, thus, sensor calibration is required for each installment. In this study, we monitored plasma impedance in situ based on the position of the vacuum variable capacitor within the matching network, without employing an external VI probe. We observed changes in the matching position according to parameter variations and subsequently confirmed that the calculated plasma impedance also varied accordingly. This study demonstrates the feasibility of real-time plasma impedance monitoring under 50 Ω-matched conditions without the use of external sensors, thereby simplifying plasma diagnostics. Full article
(This article belongs to the Special Issue Real-Time Fault Detection and Diagnosis of Industrial Electronics Equipment)
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