Mathematical Modeling of Fault Detection and Diagnosis
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 15 June 2026 | Viewed by 53
Special Issue Editor
Interests: intelligent performance monitoring of high-end equipment; industrial big data analysis and mining; industrial knowledge graph construction; artificial intelligence and deep learning
Special Issue Information
Dear Colleagues,
We are pleased to invite you contribute to the Special Issue on "Mathematical Modeling of Fault Detection and Diagnosis," which will be published in Mathematics. This Special Issue will focus on the latest advancements in mathematical modeling for fault detection and diagnosis across various systems. This Special Issue focuses on the essential role of mathematical modeling in fault detection and diagnosis across various engineering systems, addressing challenges in ensuring system reliability, safety, and efficiency.
In recent years, the application of advanced mathematical models has become crucial for improving fault detection and diagnosis. However, the inherent challenges, such as incomplete or imbalanced data and complex system behaviors, can affect the performance of these models. This Special Issue aims to highlight the latest research on mathematical approaches—such as statistical modeling, optimization techniques, machine learning, artificial intelligent and real-time diagnostic systems—to overcome these challenges and improve fault detection in manufacturing, aerospace, energy, and other industrial sectors.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:
- Mathematical modeling techniques for fault detection and diagnosis in complex engineering systems;
- Application of machine learning and artificial intelligence to improve fault diagnosis models, especially under small sample or class-imbalance;
- Statistical and optimization methods for enhancing the performance and accuracy of fault detection systems;
- Integration of real-time diagnostic systems with mathematical models for predictive maintenance;
- Advanced methods for dealing with incomplete, imbalanced, or noisy data in fault detection tasks;
- Hybrid approaches combining model-based and data-driven techniques for fault diagnosis;
- Case studies and real-world applications of mathematical modeling in fault detection across manufacturing, aerospace, and energy sectors;
- Development of multi-fidelity models for improving system reliability and fault detection efficiency;
- Applications of optimization algorithms for fault detection and diagnostic system design
I look forward to receiving your contributions.
Dr. Song Fu
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. Mathematics 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
- artificial intelligence
- fault detection
- data imbalance
- small samples
- machine learning
- statistical modeling
- data augmentation
- mathematical modeling
- sensor fusion
- industrial applications
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