P3.4 Fracture Detection of Bearings in Long-Term Measurements Using a Feature-Based CUSUM Algorithm
- Event
- SMSI 2020
-
(did not take place because of Covid-19 virus pandemic) - Band
- SMSI 2020 - Measurement Science
- Chapter
- P3 Advanced Methods and Approaches in Measurement
- Author(s)
- A. Beering, A. Zitnikov, K. Krieger - University of Bremen, Bremen (Germany)
- Pages
- 323 - 324
- DOI
- 10.5162/SMSI2020/P3.4
- ISBN
- 978-3-9819376-2-6
- Price
- free
Abstract
In this paper, a new approach for fracture detection on tapered roller bearings is presented, which is based on a feature-based CUSUM algorithm. For this purpose, experimental investigations are presented in which fractures in bearings are generated by overload. The vibration signals are recorded throughout the entire bearing lifetime in the test, from which features are later extracted and used for fracture detection. More specifically highlighted as features in this paper are the standard deviation and the clearance factor, which are often used in the context of detecting damage to rotating machinery.