Verification of measuring the bearing clearance using kurtosis, recurrences and neural networks and comparison of these approaches
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Verification of measuring the bearing clearance using kurtosis, recurrences and neural networks and comparison of these approaches. / Meier, Nicolas; Georgiadis, Anthimos; Ambrożkiewicz, Bartłomiej et al.
2019 IEEE Sensors, SENSORS 2019 - Conference Proceedings. IEEE - Institute of Electrical and Electronics Engineers Inc., 2019. 8956597 (Proceedings of IEEE Sensors; Vol. 2019-October).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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TY - CHAP
T1 - Verification of measuring the bearing clearance using kurtosis, recurrences and neural networks and comparison of these approaches
AU - Meier, Nicolas
AU - Georgiadis, Anthimos
AU - Ambrożkiewicz, Bartłomiej
AU - Litak, Grzegorz
PY - 2019/11
Y1 - 2019/11
N2 - Determination and in situ detection of bearing radial clearance are studied using vibration spectra detected by acceleration sensors applied to double-row self-aligning ball bearings. We applied three different methods for the determination of bearing clearance and present the results: a) using neural networks, b) calculating the spectral kurtosis of the corresponding spectra and c) performing recurrence plots and recurrence quantification analysis for various bearing clearances. The statistical results and corresponding quantificators show reliable in service detection and monitoring of the clearance.
AB - Determination and in situ detection of bearing radial clearance are studied using vibration spectra detected by acceleration sensors applied to double-row self-aligning ball bearings. We applied three different methods for the determination of bearing clearance and present the results: a) using neural networks, b) calculating the spectral kurtosis of the corresponding spectra and c) performing recurrence plots and recurrence quantification analysis for various bearing clearances. The statistical results and corresponding quantificators show reliable in service detection and monitoring of the clearance.
KW - Engineering
KW - Condition Monitoring and Prediction
KW - Bearing Rolling Element
KW - Ball Bearing
KW - Vibration
KW - Bearing Clearance
KW - Recurrence Plots
KW - Recurrence Quantification Analysis
KW - Neural Network
UR - http://www.scopus.com/inward/record.url?scp=85078705738&partnerID=8YFLogxK
U2 - 10.1109/SENSORS43011.2019.8956597
DO - 10.1109/SENSORS43011.2019.8956597
M3 - Article in conference proceedings
SN - 978-1-7281-1635-8
T3 - Proceedings of IEEE Sensors
BT - 2019 IEEE Sensors, SENSORS 2019 - Conference Proceedings
PB - IEEE - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE Sensors - IEEE 2019
Y2 - 27 October 2019 through 30 October 2019
ER -