Sensing Technology and Data Interpretation in Machine Diagnosis and Systems Condition Monitoring: Volume 2
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 99644
Special Issue Editors
Interests: transport; civil and mechanical engineering; vibroacoustic; noise and vibration; machine diagnostic; epidemic risk and transport safety; transport environmental issues
Special Issues, Collections and Topics in MDPI journals
Interests: development of numerical methods; modelling of optical effects; visual cryptography; nonlinear dynamical systems and chaos
Special Issues, Collections and Topics in MDPI journals
Interests: structural health monitoring; structural damage identification; smart materials and structures; applied soft computing; structural vibration and control
Special Issues, Collections and Topics in MDPI journals
Interests: mining machines; field measurements; condition monitoring; advanced signal processing; data analytics; acoustics; predictive maintenance
Special Issues, Collections and Topics in MDPI journals
Interests: machine and structure dynamics; vibro-acoustic behavior of machines and structures
Special Issues, Collections and Topics in MDPI journals
Interests: structural analysis; finite element modeling; structural dynamics; automobile engineering; nonlinear analysis; dynamic analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
I would like to interest you in this Special Issue on “Sensing Technology and Data Interpretation in Machine Diagnosis and Systems, Part 2” at Sensors and cordially invite you to submit your articles. The purpose of this second edition Special Issue is to compile studies on knowledge, research practice, and forecast development trends in the field of machine and system diagnostics, with particular emphasis on measuring systems and signal processing methods to extract useful information. The dynamic development of the Smart concept in all engineering areas indicates the need for the consolidation and exchange of knowledge in this area, for which this Special Issue is an ideal platform. Taking this into account, it was decided to launch a second edition of this Special Issue in order to showcase the development and new applications.
Machine diagnosis and systems condition monitoring are fundamental processes for decision making protocols in all mechanical systems. Control and steering of all systems determine their operational and functional activities. These decisions must be made based on proper data. Therefore, the most appropriate data must first be obtained, and then the important information components must be separated. All components of the logical decision path that may degrade the quality of the data acquired or reduce operational reliability must be avoided and eliminated. Therefore, it is important to correctly indicate the data acquisition points, select the most suitable sensors, and correctly complete the entire measurement path and dedicated signal analysis.
This Special Issue will focus on recent attempts in the development of sensors and sensing technology due to novel possibilities in machine diagnosis and systems condition monitoring to underline this new knowledge and application, especially for trends in smart machines and systems with self-diagnosis properties. An example of this is the concept of smart cities and intelligent systems, which is trending worldwide. This Special Issue will collect interdisciplinary approaches on sensors and sensing technology in machine diagnosis and systems condition monitoring, including the consideration and development of some innovative directions in research.
The potential scope includes but is not limited to the following:
- Methods and apparatuses for machine diagnosis and systems condition monitoring;
- Signal processing, data fusion, and deep learning in sensor systems;
- Damage detection and identification in machines;
- Condition monitoring in systems;
- Sensors in control and steering of the system;
- 5G/6G technologies;
- Identification of machinery non-stationary and anomalous operation;
- Advanced signal processing methods for machine diagnosis and condition monitoring;
- Practical cases of machine diagnosis and systems condition monitoring;
- Machine and system assessment under noisy conditions;
- Intelligent transport systems;
- Sensor network and relationships;
- Smart/intelligent sensors;
- Sensor technology and application for machine diagnosis and systems condition monitoring;
- Internet of Things for machine diagnosis and systems condition monitoring;
- Localization and object tracking in smart cities;
- Machine learning applications;
- Complex machine and system analysis using multiple sensors;
- Techniques for online, real-time system condition monitoring.
Prof. Dr. Rafal Burdzik
Prof. Dr. Minvydas Ragulskis
Prof. Dr. Maosen Cao
Prof. Dr. Radosław Zimroz
Dr. Chaari Fakher
Dr. Łukasz Konieczny
Guest Editors
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Keywords
- machine diagnosis
- systems condition monitoring
- sensors
- sensing technology
- smart city
- IoT
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