Bike Gear Mode Detection and Automated Chain Maintenance Using Solid-Borne Sound Analysis

Thomas Schlechter, Johannes Fischer, Pia Heins

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

Abstract

Predictive maintenance is gaining more and more importance. However, current research and implementations mostly focus on industrial applications. As high quality sensors are getting more precise and powerful, and at the same time are getting cheaper, alongside with more advanced and ubiquitous means of communication, predictive maintenance use cases in the consumer good area raise and start being more feasible. In this paper we present an idea of predictive maintenance on bike chains, applied on two typical major use cases. The proposed approach is based on solid-borne sound detection and digital analysis of chain malfunction from different causes. Finally, we identify real world use cases and appealing business models to be applied on the methodology.

Original languageEnglish
Title of host publication2020 21st International Conference on Research and Education in Mechatronics, REM 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728162249
DOIs
Publication statusPublished - 9 Dec 2020
Event21st International Conference on Research and Education in Mechatronics, REM 2020 - Cracow, Poland
Duration: 9 Dec 202011 Dec 2020

Publication series

Name2020 21st International Conference on Research and Education in Mechatronics, REM 2020

Conference

Conference21st International Conference on Research and Education in Mechatronics, REM 2020
CountryPoland
CityCracow
Period09.12.202011.12.2020

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