Machine Condition Monitoring System Based on Edge Computing Technology
The core of this publication is the design of a system for evaluating the condition of production equipment and machines by monitoring selected parameters of the production process with an additional sensor subsystem. The main positive of the design is the processing of data from the sensor layer us...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/1/180 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841548912504078336 |
|---|---|
| author | Igor Halenar Lenka Halenarova Pavol Tanuska Pavel Vazan |
| author_facet | Igor Halenar Lenka Halenarova Pavol Tanuska Pavel Vazan |
| author_sort | Igor Halenar |
| collection | DOAJ |
| description | The core of this publication is the design of a system for evaluating the condition of production equipment and machines by monitoring selected parameters of the production process with an additional sensor subsystem. The main positive of the design is the processing of data from the sensor layer using artificial intelligence (AI) and expert systems (ESs) with the use of edge computing (EC). Sensor information is processed directly at the sensor level on the monitored equipment, and the results of the individual subsystems are stored in the form of triggers in a database for use in the predictive maintenance process. The whole solution includes the design of suitable sensors and of the implementation of the sensor layer, the description of data processing algorithms, the design on the communication infrastructure for the whole system, and tests in the form of experimental operation of the device in laboratory conditions. The solution includes the visualisation of the production system status for the operator using an interactive online map. |
| format | Article |
| id | doaj-art-3f5f077d547346b6b30759267208d3fd |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-3f5f077d547346b6b30759267208d3fd2025-01-10T13:21:08ZengMDPI AGSensors1424-82202024-12-0125118010.3390/s25010180Machine Condition Monitoring System Based on Edge Computing TechnologyIgor Halenar0Lenka Halenarova1Pavol Tanuska2Pavel Vazan3Institute of Applied Informatics, Automation and Mechatronics, Faculty of Materials Science and Technology in Trnava, Slovak University of Technology in Bratislava, 812 43 Bratislava, SlovakiaInstitute of Applied Informatics, Automation and Mechatronics, Faculty of Materials Science and Technology in Trnava, Slovak University of Technology in Bratislava, 812 43 Bratislava, SlovakiaInstitute of Applied Informatics, Automation and Mechatronics, Faculty of Materials Science and Technology in Trnava, Slovak University of Technology in Bratislava, 812 43 Bratislava, SlovakiaInstitute of Applied Informatics, Automation and Mechatronics, Faculty of Materials Science and Technology in Trnava, Slovak University of Technology in Bratislava, 812 43 Bratislava, SlovakiaThe core of this publication is the design of a system for evaluating the condition of production equipment and machines by monitoring selected parameters of the production process with an additional sensor subsystem. The main positive of the design is the processing of data from the sensor layer using artificial intelligence (AI) and expert systems (ESs) with the use of edge computing (EC). Sensor information is processed directly at the sensor level on the monitored equipment, and the results of the individual subsystems are stored in the form of triggers in a database for use in the predictive maintenance process. The whole solution includes the design of suitable sensors and of the implementation of the sensor layer, the description of data processing algorithms, the design on the communication infrastructure for the whole system, and tests in the form of experimental operation of the device in laboratory conditions. The solution includes the visualisation of the production system status for the operator using an interactive online map.https://www.mdpi.com/1424-8220/25/1/180edge computingsensorspredictive maintenancemonitoringsystem |
| spellingShingle | Igor Halenar Lenka Halenarova Pavol Tanuska Pavel Vazan Machine Condition Monitoring System Based on Edge Computing Technology Sensors edge computing sensors predictive maintenance monitoring system |
| title | Machine Condition Monitoring System Based on Edge Computing Technology |
| title_full | Machine Condition Monitoring System Based on Edge Computing Technology |
| title_fullStr | Machine Condition Monitoring System Based on Edge Computing Technology |
| title_full_unstemmed | Machine Condition Monitoring System Based on Edge Computing Technology |
| title_short | Machine Condition Monitoring System Based on Edge Computing Technology |
| title_sort | machine condition monitoring system based on edge computing technology |
| topic | edge computing sensors predictive maintenance monitoring system |
| url | https://www.mdpi.com/1424-8220/25/1/180 |
| work_keys_str_mv | AT igorhalenar machineconditionmonitoringsystembasedonedgecomputingtechnology AT lenkahalenarova machineconditionmonitoringsystembasedonedgecomputingtechnology AT pavoltanuska machineconditionmonitoringsystembasedonedgecomputingtechnology AT pavelvazan machineconditionmonitoringsystembasedonedgecomputingtechnology |