Scalable validation of industrial equipment using a functional DSMS
2016 (English)In: Journal of Intelligent Information Systems, ISSN 0925-9902, E-ISSN 1573-7675, 1-25 p.Article in journal (Refereed) Epub ahead of print
A stream validation system called SVALI is developed in order to continuously validate correct behavior of industrial equipment. A functional data model allows the user to define meta-data, analyses, and queries about the monitored equipment in terms of types and functions. Two different approaches to validate that sensor readings in a data stream indicate correct equipment behavior are supported: with the model-and-validate approach anomalies are detected based on a physical model, while with learn-and-validate anomalies are detected by comparing streaming data with a model of normal behavior learnt during a training period. Both models are expressed on a high level using the functional data model and query language. The experiments show that parallel stream processing enables SVALI to scale very well with respect to system throughput and response time. The paper is based on a real world application for wheel loader slippage detection at Volvo Construction Equipment implemented in SVALI.
Place, publisher, year, edition, pages
Springer, 2016. 1-25 p.
Research subject Technology (byts ev till Engineering), Mechanical Engineering; Computer and Information Sciences Computer Science, Computer Science
IdentifiersURN: urn:nbn:se:lnu:diva-61753DOI: 10.1007/s10844-016-0427-2OAI: oai:DiVA.org:lnu-61753DiVA: diva2:1084730