Predictive maintenance with NOA: Application and insights for rotating equipment
Research output: Contribution to journal › Conference article › Contributed › peer-review
Contributors
Abstract
This paper considers an implementation of the predictive maintenance for rotating equipment in a chemical process plant by means of the NAMUR Open Architecture (NOA). Various methods and challenges for monitoring of rotating equipment are described and compared. An approach based on the motor current measurement for the use case at a BASF plant was selected due to construction limitations. The focus is on connectivity aspects as well as details of implementation of the NOA concept. Use of the NOA concept made it possible to deploy the developed monitoring system into a real plant within one day during a planned maintenance window without any permanent alterations to the existing plant. The monitoring system works in parallel and affects neither the process nor the process control directly. Discussion of the first data gathered by the installed monitoring system showed that additional context information about the process are of great importance for the comprehensive analysis. At the end of the paper, improvements with regards to the connectivity and integration of additional sensors as well as further activities such as coupling of context information about the process and development of a decision making system are discussed.
Details
Original language | English |
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Pages (from-to) | 761-767 |
Number of pages | 7 |
Journal | IEEE International Conference on Emerging Technologies and Factory Automation, ETFA |
Publication status | Published - Sept 2020 |
Peer-reviewed | Yes |
Conference
Title | 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation |
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Abbreviated title | ETFA 2020 |
Conference number | 25 |
Duration | 8 - 11 September 2020 |
Website | |
Degree of recognition | International event |
Location | TU Wien & online |
City | Vienna |
Country | Austria |
External IDs
ORCID | /0000-0001-5165-4459/work/142248239 |
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Keywords
ASJC Scopus subject areas
Keywords
- modelling, motor current analysis, NOA, predictive maintenance, process industry, rotating equipment