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Abstract
The strive for autonomous operation of machines, vehicles and ships requires a leap in the level of self-diagnostics and situation awareness. This self-diagnostic does not directly add value in form of increased performance but is however necessary for safe operations. Hence, there is a need for implementing self-diagnostics systems using non-expensive equipment. In this paper, we present the design, implementation and installation of a vibration sensing system in a machine room of a cruise ferry. The objective of this installation was to validate our assumption that machine room monitoring can be achieved using non-expensive components and reach consistency and reliability of data output from this system. The reliability would be reached by redundancy of sensors, and intelligent data fusion close to the sensor nodes using edge computing. The emphasis in this paper is on the practical design and implementation of the system including sensors, cabling, edge computing nodes and on ship storage of data. The implementation of the analytics and sensor fusion will be presented in a later paper. As a result, we present how the system has worked and generated data for the just under 6 months' time the system has been running in the cruise ferry.
Original language | English |
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Title of host publication | 12th Symposium on High-Performance Marine Vehicles |
Subtitle of host publication | HIPER’20 |
Editors | Bertram Volker |
Publisher | Technische Universität Hamburg-Harburg |
Pages | 239-250 |
Number of pages | 12 |
ISBN (Electronic) | 978-3-89220-718-4 |
Publication status | Published - 14 Oct 2020 |
MoE publication type | A4 Article in a conference publication |
Event | Symposium on High-Performance Marine Vehicles: HIPER - Duration: 12 Oct 2020 → 14 Oct 2020 |
Conference
Conference | Symposium on High-Performance Marine Vehicles |
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Period | 12/10/20 → 14/10/20 |
Keywords
- 0
Fingerprint
Dive into the research topics of 'Edge-based Vibration Monitoring of Marine Vessel Engines'. Together they form a unique fingerprint.Projects
- 1 Finished
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EDGE: Edge Analytics for Smart Diagnostics in Digital Machinery Concept
Björkqvist, J. (Principal Investigator), Lundell, A. (Co-Principal Investigator) & Morariu, A.-R. (Co-Investigator)
01/10/18 → 28/02/21
Project: Research