Ball bearing vibration data for detecting and quantifying spall faults

Mohamed A A Ismail; Jens Windelberg; Andreas Bierig; Iñaki Bravo; Aitor Arnaiz

doi:10.1016/j.dib.2023.109019

Ball bearing vibration data for detecting and quantifying spall faults

Data Brief. 2023 Mar 1:47:109019. doi: 10.1016/j.dib.2023.109019. eCollection 2023 Apr.

Authors

Mohamed A A Ismail¹, Jens Windelberg¹, Andreas Bierig¹, Iñaki Bravo², Aitor Arnaiz²

Affiliations

¹ German Aerospace Center (DLR) - Institute of Flight Systems, Lilienthalplatz 7, 38108 Braunschweig, Germany.
² Intelligent Information Systems, TEKNIKER, Eibar, 20600, Spain.

Abstract

Ball bearings are essential components of electromechanical systems, and their failures significantly affect the service lifetime of these systems. For highly reliable and safety-critical electromechanical systems in energy and aerospace sectors, early bearing fault detection and quantification are crucial. The vibration measurements of bearing fatigue faults, i.e., spalls, are typically induced by multiple excitation mechanisms depending on the fault size and the operating conditions. This data article contains vibration datasets for faulty ball bearings, including the common vibration excitation mechanisms for various fault sizes and operating conditions. These faults are artificially seeded on bearing races by a precise machining process to emulate realistic fatigue faults. This data article is beneficial for better understanding the vibration signal characteristics under different fault sizes and for validating condition monitoring methods for various industrial and aerospace applications.

Keywords: Bearing defects; Condition monitoring; Health assessment; Predictive maintenance.