Sensor Faults Detection in Industrial Condition Monitoring and Diagnosing Systems
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Industrial Sensors".
Deadline for manuscript submissions: 31 May 2025 | Viewed by 918
Special Issue Editors
Interests: fault diagnosis
Interests: technical diagnostic; vibration acoustic; modal analysis; signal and image analysis
Special Issue Information
Dear Colleagues,
With the advent of Industry 4.0, there has been an increased interest in systems for monitoring and diagnosing machines and processes that enable the implementation of predictive and prescriptive maintenance. These systems often allow for cloud data collection and the implementation of analytical methods based on machine learning and artificial intelligence techniques. The effectiveness of computational algorithms depends on the quality of the data, which comes from measurement systems comprising both analog and digital sensors installed at various points of a machine or the installation and measuring of different physical quantities. Industrial sensors often operate in harsh conditions, subjected to both mechanical and chemical influences, which can lead to damage and reduced measurement accuracy. Therefore, an essential aspect of measurement system operation is diagnosing their functionality. This Special Issue’s aim is to present review articles and original papers discussing the latest research results and discoveries in the field monitoring and self-diagnosing methods for the condition of sensors used in industrial monitoring systems.
Dr. Tomasz Barszcz
Dr. Marek Fidali
Dr. Piotr Przystalka
Guest Editors
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Keywords
- fault detection
- condition monitoring
- fault-tolerant control
- sensor self-diagnostics
- embedded systems
- smart sensors
- sensor design
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