Analysis of Acceleration Data Using Low-Power Embedded Devices to Detect Gear Faults

Bernhard Rupprecht, Stefan Sendlbeck, Birgit Vogel-Heuser, Ralf Brederlow, Erich Knoll, Karsten Stahl

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Gear condition monitoring can prevent unexpected downtimes or sudden failure of machinery. Since gear damage usually results from tooth contact, data for reliable fault detection should be acquired as close as possible to this engagement to reduce other components' disturbances (such as vibrations). One typical gear damage mechanism is pitting. Although the detection of gear pitting using acceleration data is already covered in research, methods with integrated sensors and electronics into the gear (in-situ) are still in their infancy. Most fault detection approaches still rely on external high-performance measurement systems unsuitable for in-situ integration. Thus, this paper proposes an algorithm pipeline for detecting gear pitting using acceleration data suitable for low-power embedded devices, such as Microcontrollers (MCUs). Downsampling provides the minimum required acceleration data sample rate necessary for detection. It is the basis for future work on suitable sensor and hardware selection. Finally, implementing the algorithm pipeline on a PC and a low-power ARM-Cortex M0+ MCU shows its applicability.

Original languageEnglish
Title of host publication2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023
PublisherIEEE Computer Society
ISBN (Electronic)9798350320695
DOIs
StatePublished - 2023
Event19th IEEE International Conference on Automation Science and Engineering, CASE 2023 - Auckland, New Zealand
Duration: 26 Aug 202330 Aug 2023

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2023-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference19th IEEE International Conference on Automation Science and Engineering, CASE 2023
Country/TerritoryNew Zealand
CityAuckland
Period26/08/2330/08/23

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