Novel Approaches for Fault Diagnostics of Machine Elements
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".
Deadline for manuscript submissions: 30 April 2025 | Viewed by 10
Special Issue Editors
Interests: electric properties of tribosystems; sensing machine elements; sensor integration; design for additive manufacturing; potential of additive technologies; respective development methods
Interests: lightweight design; smart structures; vibration and noise control; reliability engineering and SHM
Special Issues, Collections and Topics in MDPI journals
Interests: health and usage monitoring; prognostics and health management; predictive maintenance; reliability engineering
Interests: lightweight design; smart structures; active and passive vibration technologies; design methodologies
Special Issues, Collections and Topics in MDPI journals
Interests: machine elements; smart machine elements; rolling bearings; transmissions; condition monitoring; RUL prediction; predictive maintenance
Special Issue Information
Dear Colleagues,
Faults of machine elements are considered a major root cause in all technical equipment, causing considerable economic damage. The reduction of unexpected and unnecessary maintenance intervals is one of the major opportunities to improve productivity or profitability. Hence, extensive research has been decidated to the development of new methods to detect faults earlier, preferably before the consecutive breakdown of technical systems. However, in most cases, fault diagnosis of machine elements (the backbone of technical systems) is restricted to conventional vibration analysis in lower frequency bands, which often requires a significant fault to detect changes in the characteristic sound and vibration finger print of a machine.
The target of this Special Issue is to compile a comprehensive overview of contemporary and novel approaches to fault diagnostic of machine elements. The focus is on non-destructive measuring, evaluation, and signal processing techniques. In addition, the approaches must, at least, be verified in typical machine element applications. The algorithms need to be validated in experiments to provide results superior to the current state of research.
Prof. Dr. Eckhard Kirchner
Prof. Dr. Tobias Melz
Prof. Dr. Uwe Klingauf
Dr. Sven Herold
Guest Editors
Florian Michael Becker-Dombrowsky
Guest Editor Assistant
Manuscript Submission Information
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Keywords
- fault diagnosis
- impedance measurement
- predictive maintenance
- predictive health monitoring
- non-destructive measurement
- feature engineering
- rolling element bearings
- plain and journal bearings
- involute gears
- bevel and worm gear drives
- shiftable and non shiftable clutches
- shaft–hub connections
- sealing components
