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Article

Beamforming Applied to Ultrasound Analysis in Detection of Bearing Defects

1
FTI-CoSys Lab, University of Antwerp, 2020 Antwerp, Belgium
2
Flanders Make Strategic Research Centre, 3920 Lommel, Belgium
3
Department of Electrical Energy, Metals, Mechanical Constructions and Systems, Ghent University, 9000 Ghent, Belgium
*
Author to whom correspondence should be addressed.
Member of EEDT partner of Flanders Make, www.eedt.ugent.be.
Sensors 2021, 21(20), 6803; https://doi.org/10.3390/s21206803
Received: 27 August 2021 / Revised: 1 October 2021 / Accepted: 5 October 2021 / Published: 13 October 2021
(This article belongs to the Section Electronic Sensors)
The bearings of rotating machinery often fail, leading to unforeseen downtime of large machines in industrial plants. Therefore, condition monitoring can be a powerful tool to aid in the quick identification of these faults and make it possible to plan maintenance before the fault becomes too drastic, reducing downtime and cost. Predictive maintenance is often based on information gathered from accelerometers. However, these sensors are contact-based, making them less attractive for use in an industrial plant and more prone to breakage. In this paper, condition monitoring based on ultrasound is researched, where non-invasive sensors are used to record the noise originating from different defects of the Machinery Fault Simulator. The acoustic data are recorded using a sparse microphone array in a lab environment. The same array was used to record real spatial noise in a fully operational plant which was later added to the acoustic data containing the different defects with a variety of Signal To Noise ratios. In this paper, we compare the classification results of the noisy acoustic data of only one microphone to the beamformed acoustic data. We do this to investigate how beamforming could improve the classification process in an ultrasound condition-monitoring application in a real industrial plant. View Full-Text
Keywords: acoustic signal processing; array signal processing; beamforming; microphone arrays; predictive maintenance acoustic signal processing; array signal processing; beamforming; microphone arrays; predictive maintenance
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MDPI and ACS Style

Verellen, T.; Verbelen, F.; Stockman, K.; Steckel, J. Beamforming Applied to Ultrasound Analysis in Detection of Bearing Defects. Sensors 2021, 21, 6803. https://doi.org/10.3390/s21206803

AMA Style

Verellen T, Verbelen F, Stockman K, Steckel J. Beamforming Applied to Ultrasound Analysis in Detection of Bearing Defects. Sensors. 2021; 21(20):6803. https://doi.org/10.3390/s21206803

Chicago/Turabian Style

Verellen, Thomas, Florian Verbelen, Kurt Stockman, and Jan Steckel. 2021. "Beamforming Applied to Ultrasound Analysis in Detection of Bearing Defects" Sensors 21, no. 20: 6803. https://doi.org/10.3390/s21206803

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