Ontology – based context resolution in internet of things enabled diagnostics

Date

2020-12-18

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier

Department

Type

Article

ISSN

2405-8963

Format

Free to read from

Citation

Al-Shdifat A, Emmanouilidis C, Khan M, Starr AG. (2020) Ontology – based context resolution in internet of things enabled diagnostics. IFAC-PapersOnLine, Volume 53, Issue 3, 2020, pp. 251-256

Abstract

Internet of things (IoT)-generated data from industrial systems are often collected in non-actionable form, thus not directly aiding maintenance actions. Context information management is often seen as an enabler for interoperability and context-based service adaptation, acting as a mechanism for linking data with knowledge to adaptive data and services. Ontology-based approaches for semantic maintenance have been proposed in the past as a data and service mediation mechanism and are adopted here as the starting point employed to develop a context resolution service for industrial diagnostics. The underlying ontology of the context resolution mechanism is relevant to failure analysis of mechanical components. The terminology and relationship between concepts are structured on the basis of relevant standards with a reliability-oriented knowledge grounding. A reasoning mechanism is employed to deliver context resolution and the derived context can add a metadata layer on data or events generated by automated and human-driven means. The approach is applied on a gearbox test rig appropriate for emulating complex misalignment cases met in many manufacturing and aerospace applications

Description

Software Description

Software Language

Github

Keywords

Industrial Diagnostics, Maintenance Ontology, Context Management

DOI

Rights

Attribution-NonCommercial-NoDerivatives 4.0 International

Relationships

Relationships

Supplements

Funder/s