Vision Based Defect Detection in Power Systems
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Industrial Sensors".
Deadline for manuscript submissions: 30 November 2026 | Viewed by 903
Special Issue Editors
Interests: electric artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The reliability and security of power systems are key to ensuring the sustainable and stable operation of modern infrastructure. Long-term exposure of transmission, transformation and distribution equipments to harsh natural environment will inevitably lead to aging, corrosion, structural damage and other defects over time. If these defects are not identified and evaluated timely and accurately, the consequences may range from reduced energy efficiency and increased operation and maintenance costs to local failures and even large-scale power outages, resulting in significant economic losses and social operation interruption. Therefore, regular inspection of these equipments and timely repair of defects are very important to ensure the safe and reliable operation of power system.
In recent years, rapid advances in computer vision, artificial intelligence, robotics and sensor technology have provided innovative solutions to these longstanding challenges. The Vision‑Based Defect Detection in Power Systems (VDDPS) method utilizes drones, inspection robots or fixed monitoring systems equipped with high‑resolution cameras, infrared thermal imagers, LiDAR and other sensors to efficiently capture high‑precision visual data from power assets. By processing this data with advanced deep learning models, VDDPS significantly enhances the efficiency, accuracy and safety of inspection operations.
This Special Issue aims to assemble the latest research advances, innovative solutions and practical experiences in the field of VDDPS, creating a high‑level platform for scholarly exchange and fostering deeper application and continued progress in this domain. We welcome original contributions that explore various facets of VDDPS, including, but not limited to, the following:
- VDDPS in challenging and complex environments;
- VDDPS with multimodal data fusion techniques;
- Lightweight model design for VDDPS;
- Few-shot or zero-shot learning in VDDPS;
- High-resolution image processing for VDDPS;
- Self-supervised and contrastive learning for VDDPS;
- Human-in-the-loop and interactive VDDPSs;
- Interpretable and explainable AI models in VDDPS;
- Vision enhancement techniques under adverse weather and lighting conditions;
- Three-dimensional data processing based on LiDAR point clouds;
- Benchmark datasets and evaluation metrics for VDDPS.
Prof. Dr. Zhenbing Zhao
Dr. Shiyin Zhang
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 250 words) can be sent to the Editorial Office for assessment.
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. Sensors 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 2600 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
- defect detection
- power systems
- transmission
- transformation and distribution equipments
- computer vision
- artificial intelligence
- multimodal data fusion
- 3D data processing
- explainable AI models
- high-resolution
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
