Advanced Sensing Technology for Fault Diagnosis in Complex Mechanical Systems
A Special Issue of Sensors (ISSN 1424-8220) belonging to the section "Fault Diagnosis & Sensors".
Deadline for manuscript submissions: 31 March 2027 | Viewed by 34
Editors
Interests: prognostics and health management; fault diagnosis; structural health monitoring; data-driven model; signal processing
Interests: prognostics and health management; reliability engineering for space systems; structural health monitoring
Special Issue Information
Dear Colleagues,
As mechanical equipment is increasingly deployed in extreme operating environments, equipment maintenance and health management have become a highly valuable area of research. In this context, advanced sensing technologies and data-driven methods play a crucial role in enabling fault diagnosis for complex mechanical systems. The continuous evolution of sensor networks provides massive, multi-dimensional condition monitoring data, while advanced data-driven algorithms transform these raw signals into health insights. This synergy improves the accuracy of fault detection, ensuring the long-term safety and reliability of critical mechanical equipment. We invite you to submit your latest research contributions to this upcoming Special Issue, which covers all aspects of sensing technologies and data-driven fault diagnosis. Full-length papers, communications and reviews are welcome.
This Special Issue aims to bring together the latest advances in the field of data-driven fault diagnosis and sensors, covering basic research, technological development and innovative applications. The reviews must provide a key overview of the latest technologies related to the technology and application of diagnosis and sensors.
The topics of interest include, but are not limited to, the following:
- Development and application of novel smart sensors;
- Multi-sensor data fusion and multi-modal information processing;
- Sensor network optimization, layout design and sensor self-calibration techniques;
- Edge computing and intelligent signal processing at the sensor node;
- Advanced sensing technologies for extreme operating environments;
- Advanced signal processing and feature extraction;
- Condition monitoring and fault diagnosis under complex conditions.
Dr. Zhe Wang
Dr. Peng Li
Dr. Yiming Xiao
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-anonymized 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
- fault diagnosis
- multi-sensor data fusion
- condition monitoring
- signal processing
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