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A Vibration Based Automatic Fault Detection Scheme for Drilling Process Using Type-2 Fuzzy Logic
Gas Turbine and Transmission Research Centre, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK.ORCID iD: 0000-0003-4720-0897
Gas Turbine and Transmission Research Centre, Faculty of Engineering, University of Nottingham, Nottingham, NG7 2RD, United Kingdom.
Department of Applied Physics and Electronics, Umeå Universitet, Umeå, 90187, Sweden.ORCID iD: 0000-0003-2960-3094
School of Science and Technology, Orebro University, Orebro, 70182, Sweden.ORCID iD: 0000-0002-2014-1308
2022 (English)In: Algorithms, E-ISSN 1999-4893, Vol. 15, no 8, p. 284-284Article in journal (Refereed) Published
Abstract [en]

The fault detection system using automated concepts is a crucial aspect of the industrial process. The automated system can contribute efficiently in minimizing equipment downtime therefore improving the production process cost. This paper highlights a novel model based fault detection (FD) approach combined with an interval type-2 (IT2) Takagi–Sugeno (T–S) fuzzy system for fault detection in the drilling process. The system uncertainty is considered prevailing during the process, and type-2 fuzzy methodology is utilized to deal with these uncertainties in an effective way. Two theorems are developed; Theorem 1, which proves the stability of the fuzzy modeling, and Theorem 2, which establishes the fault detector algorithm stability. A Lyapunov stabilty analysis is implemented for validating the stability criterion for Theorem 1 and Theorem 2. In order to validate the effective implementation of the complex theoretical approach, a numerical analysis is carried out at the end. The proposed methodology can be implemented in real time to detect faults in the drilling tool maintaining the stability of the proposed fault detection estimator. This is critical for increasing the productivity and quality of the machining process, and it also helps improve the surface finish of the work piece satisfying the customer needs and expectations.

Place, publisher, year, edition, pages
2022. Vol. 15, no 8, p. 284-284
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-64199DOI: 10.3390/a15080284ISI: 000846411300001Scopus ID: 2-s2.0-85137265416OAI: oai:DiVA.org:mdh-64199DiVA, id: diva2:1795063
Available from: 2023-09-07 Created: 2023-09-07 Last updated: 2023-09-11Bibliographically approved

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Paul, Satyam

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