Abstract
Data collection and analysis are critical for identifying and diagnosing issues in rolling-element bearings. Vishwakarma Technologies, Pune, India, has developed a unique rolling-element vibration dataset specifically gathered under controlled static load and motion conditions, adding significant value to existing public datasets. This dataset offers researchers precise vibration data that complements existing features, enabling accurate assessments of bearing conditions. Collected using accelerometers, the dataset also provides insights into bearing deterioration under sustained loads, which can help predict failures and support the development of advanced diagnostic tools. The dataset comprises 50 files that cover a wide range of operating and fault conditions, including varying motor speeds, high-loading scenarios, and both healthy and faulty bearing states. It delivers detailed, high-quality information that enhances the detection and diagnosis of rolling-element bearing problems, contributing to more reliable maintenance practices and improved system reliability.