Fault Diagnosis and Detection of Machinery
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".
Deadline for manuscript submissions: 20 April 2024 | Viewed by 6118
Special Issue Editors
Interests: fault detection of machinery; vibration-based condition monitoring; mechanical systems modeling; bearing analysis
Special Issues, Collections and Topics in MDPI journals
Interests: nonlinear dynamics; shells and plates; carbon nanotubes; functionally graded materials; vibration-based condition monitoring; mechanical systems modeling; stability analysis; damping
Special Issues, Collections and Topics in MDPI journals
Interests: fault detection of machinery; vibration-based condition monitoring; mechanical systems modeling; gear analysis
Special Issue Information
Dear Colleagues,
This Special Issue focuses on sharing advances, results and perspectives in the field of condition monitoring of mechanical systems. Although most of the critical components have been widely analyzed, new applications are proposed in the industrial field and always pose new challenges to diagnostics in terms of complexity, harsh environment, and non-stationary working conditions, among others. An example is the diagnostics of a fleet of machines in a closed environment. Strong non-stationarity of the motion profile or of the dynamic loads, vibration interference from close devices, or inability to properly sensor the moving elements make the condition monitoring challenging.
The target of the Special Issue is to collect novel contributions for all the steps of the fault diagnosis and detection process. An indicative list may include the development of specific sensors, hardware setup, data analytics, physical modelling, data processing and data fusion. Papers on machine learning approaches to diagnostics are accepted but the physical parameters that determine the success of the methodology proposed should be evident. Although advances have been made in other fields—such as MCSA—this Special Issue is mainly focused on the vibration-based condition monitoring of mechanical/mechatronics systems. Other types of signals/sensors are allowed as long as they are necessary for the vibrational analysis.
The experimental dataset is not accessible to all researchers but several free collections are available online. We suggest, for example, the Polito Bearing Dataset (Politecnico di Torino, Italy), available through the following link:
ftp://ftp.polito.it/people/DIRG_BearingData/
It comprises both tests at different fault levels and a complete lifetime of a bearing set.
Dr. Marco Cocconcelli
Dr. Matteo Strozzi
Dr. Gianluca D’Elia
Guest Editors
Manuscript Submission Information
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Keywords
- damage identification
- damage prediction
- gear/bearing diagnostics
- remaining useful life
- digital twins for diagnostics/prognostics
- physics-enhanced machine learning
- variable speed conditions
- non-stationary signal processing
- cyclostationarity
- diagnostic algorithms
- mechatronic systems
- rotor dynamics
- stability analysis