Publications:Monitoring equipment operation through model and event discovery

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Title Monitoring equipment operation through model and event discovery
Author Sławomir Nowaczyk and Anita Sant'Anna and Ece Calikus and Yuantao Fan
Year 2018
PublicationType Conference Paper
Journal
HostPublication Intelligent Data Engineering and Automated Learning – IDEAL 2018 : 19th International Conference, Madrid, Spain, November 21–23, 2018, Proceedings, Part II
Conference Intelligent Data Engineering and Automated Learning – IDEAL 2018, 19th International Conference, Madrid, Spain, November 21–23, 2018
DOI http://dx.doi.org/10.1007/978-3-030-03496-2_6
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:1276685
Abstract Monitoring the operation of complex systems in real-time is becoming both required and enabled by current IoT solutions. Predicting faults and optimising productivity requires autonomous methods that work without extensive human supervision. One way to automatically detect deviating operation is to identify groups of peers, or similar systems, and evaluate how well each individual conforms with the group. We propose a monitoring approach that can construct knowledge more autonomously and relies on human experts to a lesser degree: without requiring the designer to think of all possible faults beforehand; able to do the best possible with signals that are already available, without the need for dedicated new sensors; scaling up to “one more system and component” and multiple variants; and finally, one that will adapt to changes over time and remain relevant throughout the lifetime of the system. © Springer Nature Switzerland AG 2018.