| Bibliography | Wilhelm, Yannick; Reimann, Peter; Gauchel, Wolfgang; Mitschang, Bernhard: Overview on Hybrid Approaches to Fault Detection and Diagnosis: Combining Data-driven, Physics-based and Knowledge-based Models.
In: Procedia CIRP: Proceedings of the 14th CIRP Conference on Intelligent Computation in Manufacturing Engineering (CIRP ICME).
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
english.
Elsevier BV, July 2020.
Article in Proceedings (Conference Paper).
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| CR-Schema | H.2.8 (Database Applications)
I.2.1 (Applications and Expert Systems)
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| Keywords | Fault Detection; Fault Diagnosis; Hybrid Methods; Diagnostics and Maintenance; Knowledge-driven Methods; Machine Learning |
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| Abstract | In this paper, we review hybrid approaches for fault detection and fault diagnosis (FDD) that combine data-driven analysis with physics-based and knowledge-based models to overcome a lack of data and to increase the FDD accuracy. We categorize these hybrid approaches according to the steps of an extended common workflow for FDD. This gives practitioners indications of which kind of hybrid FDD approach they can use in their application.
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| Department(s) | University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems
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| Project(s) | GSaME-NFG
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| Entry date | June 23, 2020 |
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