TY - CHAP U1 - Konferenzveröffentlichung A1 - Schwendemann, Sebastian A1 - Rausch, Andreas A1 - Sikora, Axel T1 - Detailed Study of Different Degradation Stages of Bearings in a Practical Reference Dataset T2 - 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA) N2 - The often-occurring short-term orders of manufactured products require a high machine availability. This requirement increases the importance of predictive maintenance solutions for bearings used in machines. There are, among others, hybrid solutions that rely on a physical model. For their usage, knowing the different degradation stages of bearings is essential. This research analyzes the underlying failure mechanisms of these stages theoretically and in a practical example of the well-known FEMTO dataset used for the IEEE PHM 2012 Data Challenge to provide this knowledge. In addition, it shows for which use cases the usage of low-frequency accelerometers is sufficient. The analysis provides that the degradation stages toward the end of the bearing life can also be detected with low-frequency accelerometers. Further, the importance of high-frequency accelerometers to detect bearing faults in early degradation stages is pointed out. These aspects have not been paid attention to by industry and research until now, despite providing a considerable cost-saving potential. KW - bearing KW - accelerometer KW - degradation stages KW - predictive maintenance KW - RUL KW - Failure analysis KW - Manufacturing automation Y1 - 2023 SN - 1946-0759 (Elektronisch) SS - 1946-0759 (Elektronisch) SN - 1946-0740 (Print on Demand) SS - 1946-0740 (Print on Demand) SN - 979-8-3503-3991-8 (Elektronisch) SB - 979-8-3503-3991-8 (Elektronisch) SN - 979-8-3503-3990-1 (USB) SB - 979-8-3503-3990-1 (USB) SN - 979-8-3503-3992-5 (Print on Demand) SB - 979-8-3503-3992-5 (Print on Demand) U6 - https://doi.org/10.1109/ETFA54631.2023.10275478 DO - https://doi.org/10.1109/ETFA54631.2023.10275478 SP - 1 EP - 8 PB - IEEE ER -