Failure Diagnosis of Complex Systems
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Signal and Data Analysis".
Deadline for manuscript submissions: 31 October 2025 | Viewed by 90
Special Issue Editor
Interests: fault diagnosis of power systems and electrical equipment; safe and stable operation of smart grids and energy Internets; application of artificial intelligence technology in power systems and integrated energy systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Modern complex systems, ranging from industrial machinery and power grids to autonomous vehicles and the healthcare network, are increasingly intertwined with nonlinear dynamics, interdependencies, and high uncertainty. While these systems drive technological innovation, their susceptibility to unexpected failures poses significant challenges to reliability, safety, and efficiency. Timely and accurate failure diagnosis is critical yet remains a formidable task due to the interplay of noisy data, model inaccuracies, and emergent behaviors in complex systems.
This Special Issue invites contributions addressing novel theories, methodologies, and applications in failure diagnosis for complex systems. Submissions should emphasize rigorous mathematical foundations, scalability, and real-world applicability. Interdisciplinary insights bridging entropy, nonlinear dynamics, statistical mechanics, and information theory are particularly encouraged. By fostering advancements in fault diagnosis frameworks, this issue aims to enhance robustness in critical infrastructures and accelerate the transition to intelligent, self-diagnosing systems. We welcome original research articles, reviews, and perspectives from academia and industry. Topics of interest include, but are not limited to, the following:
- fault detection and diagnosis methods for complex systems based on information theory and entropy analysis
- data-driven prognostics and health management technology
- condition monitoring and fault location technologies for key equipment in smart grids
- real-time fault diagnosis framework for complex systems driven by digital twins
- deep learning-based multimodal fault feature extraction and classification algorithms
- machine learning/AI-enhanced diagnostics (e.g., deep learning and reinforcement learning)
- application of complex network theory in fault propagation analysis of critical infrastructures
- fault pattern recognition and fault-tolerant control for new energy systems (e.g., wind turbines and photovoltaic arrays)
Prof. Dr. Tao 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. Entropy is an international peer-reviewed open access monthly 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
- information theory
- entropy
- deep learning
- nonlinear dynamics
- fault detection
- fault diagnosis
- fault pattern recognition
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.
