Ismail Mohamed A A, Windelberg Jens, Bierig Andreas, Bravo Iñaki, Arnaiz Aitor
German Aerospace Center (DLR) - Institute of Flight Systems, Lilienthalplatz 7, 38108 Braunschweig, Germany.
Intelligent Information Systems, TEKNIKER, Eibar, 20600, Spain.
Data Brief. 2023 Mar 1;47:109019. doi: 10.1016/j.dib.2023.109019. eCollection 2023 Apr.
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.
滚珠轴承是机电系统的关键部件,其故障会显著影响这些系统的使用寿命。对于能源和航空航天领域中高度可靠且对安全至关重要的机电系统而言,早期轴承故障检测和量化至关重要。轴承疲劳故障(即剥落)的振动测量通常由多种激励机制引起,这取决于故障尺寸和运行条件。本文包含有故障滚珠轴承的振动数据集,包括各种故障尺寸和运行条件下常见的振动激励机制。这些故障通过精确加工工艺人工植入轴承滚道,以模拟实际的疲劳故障。本文有助于更好地理解不同故障尺寸下的振动信号特征,并验证适用于各种工业和航空航天应用的状态监测方法。