A multi-condition acoustic dataset of ball bearings for fault diagnosis

This work provides a multi-condition, long-duration acoustic dataset for ball bearings, covering five states: normal, cage fracture, inner race pitting, outer race pitting, and compound inner-outer race pitting. These data were acquired separately for each of the combinations of three rotational speeds (800, 1000, and 1200 r/min) and three load levels (0%, 15%, and 30% of the rated torque, where 100% corresponds to 6 Nm). Acoustic signals were synchronously recorded using two B&K 4966 and one CRY333 microphones, with a continuous 50-minute recording for each of the 45 operational conditions at a sampling rate of 32,768 Hz. The raw data are provided in the proprietary .bkc format, with a total duration of 2250 minutes. Files are organized in a hierarchical directory structure (speed-load-fault type) and accompanied by metadata tables. The dataset supports tasks such as feature extraction, pattern recognition, and can serve as a benchmark for developing and validating fault diagnosis algorithms for rotating machinery, particularly for evaluating model performance across varying operating conditions.