Technical Diagnostics and Predictive Maintenance, 2nd Edition
A special issue of Applied Sciences (ISSN 2076-3417).
Deadline for manuscript submissions: 31 January 2026 | Viewed by 13
Special Issue Editors
Interests: technical diagnostics; virtual instrumentation; mechanical engineering; nanomaterials
Special Issues, Collections and Topics in MDPI journals
Interests: monitoring and control of machines; mechatronic systems
Special Issues, Collections and Topics in MDPI journals
Interests: data acquisition; digital twins; identification technologies
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The main aim of this Special Issue is to present the state of the research on the topics of theory, modelling, monitoring, and diagnostics of the operation of technical systems, data processing, and analysis focused on faults detection, along with predictive maintenance theory and methods.
Research subjects should be investigated by using specific models, tools, and instruments, along with their verification and evaluation of the operational states of technical systems. The knowledge presented in this Special Issue, as well as methods, technical systems, and their applications, vindicates its strong potential to attract and impress researchers as well as other professionals, and will contribute to the process of giving answers that are still to be given or questions that are still to be formulated.
Contributions should primarily focus on:
- Technical diagnostic methods and systems
- Diagnostics of machines and technical systems operational states
- Optimization of machinery operation and service using diagnostic methods
- Use of novel methods and technologies in technical diagnostics and maintenance
- Online monitoring, digital twin, data acquisition, and signal processing
- Machine learning and AI-based methods in technical diagnostics and predictive maintenance
- Diagnostic and maintenance utilization of virtualized systems
- Advanced inspection methods
- Diagnostics of drives (electric, pneumatic, etc.)
- Technical systems operation quality and reliability assessment
- Technical systems operation modelling and characterization
- Functional surface properties characterization
- Structural characterization of materials for defects identification
- Aspects of implementing technical diagnostics and predictive maintenance
- Safety and health protection aspects of diagnostics and maintenance
Dr. Tibor Krenicky
Prof. Dr. Ján Piteľ
Dr. Kamil Židek
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. Applied Sciences 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
- technical diagnostics
- predictive maintenance
- machine learning
- operational states
- technical system reliability
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Related Special Issue
- Technical Diagnostics and Predictive Maintenance in Applied Sciences (9 articles)
