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Authors: Zrinka Murat ; Danko Brezak ; Goran Augustin and Dubravko Majetic

Affiliation: University of Zagreb, Croatia

ISBN: 978-989-758-212-7

Keyword(s): Bone Drilling, Drill Wear, Acoustic Emission, Neural Networks, Data Mining.

Related Ontology Subjects/Areas/Topics: Acoustic Signal Processing ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Detection and Identification ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Monitoring and Telemetry ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing

Abstract: Medical drills are subject to wear process due to mechanical, thermal and, potentially, sterilisation influences. The influence of drill wear on friction contributes to the drilling temperature rise and occurrence of thermal osteonecrosis. During the cutting process drilling temperature cannot be adequately reduced by applying cooling fluid externally on the bone surface and a part of a tool which is not in the contact with the bone if higher wear rates occurs. Since it is not possible to directly establish or measure drill wear rate without interrupting the machining process, this important parameter should be estimated using available process signals. Therefore, the application of tool wear features extracted from acoustic emission signals in the frequency domain for the purpose of indirect medical drill wear monitoring process has been studied in detail and the results are presented in this paper.

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Paper citation in several formats:
Murat Z., Brezak D., Augustin G. and Majetic D. (2017). Frequency Domain Analysis of Acoustic Emission Signals in Medical Drill Wear Monitoring.In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2017) ISBN 978-989-758-212-7, pages 173-177. DOI: 10.5220/0006150401730177

@conference{biosignals17,
author={Zrinka Murat and Danko Brezak and Goran Augustin and Dubravko Majetic},
title={Frequency Domain Analysis of Acoustic Emission Signals in Medical Drill Wear Monitoring},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2017)},
year={2017},
pages={173-177},
publisher={ScitePress},
organization={INSTICC},
doi={10.5220/0006150401730177},
isbn={978-989-758-212-7},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOSIGNALS, (BIOSTEC 2017)
TI - Frequency Domain Analysis of Acoustic Emission Signals in Medical Drill Wear Monitoring
SN - 978-989-758-212-7
AU - Murat Z.
AU - Brezak D.
AU - Augustin G.
AU - Majetic D.
PY - 2017
SP - 173
EP - 177
DO - 10.5220/0006150401730177

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