A multi-condition acoustic dataset of ball bearings for fault diagnosis-compound inner-outer race pitting

Description

This dataset provides multi-condition, long-duration acoustic data for ball bearings. The data were acquired from bearings with normal bearing faults, systematically and separately for each combination 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 N·m). Acoustic signals were recorded synchronously using three microphones: two B&K Type 4966 and one CRY333. The sensitivities were 49.76 mV/Pa (B&K at Position 2), 46.95 mV/Pa (B&K at Position 3), and 23.98 mV/Pa (CRY333at Position 1), respectively. The detailed microphone placement is described in our associated dataset article to be published in Data in Brief. For each of the nine operational conditions, a continuous 50-minute recording was captured at a sampling rate of 32,768 Hz. For data management, each 50-minute recording is segmented into five sequential 10-minute files (labeled 1-5) within the repository. The raw data are provided in the proprietary .bkc format. Files are organized and named according to a hierarchical directory structure based on fault type, speed, load, and sampling rate. This dataset supports analytical tasks such as feature extraction and pattern recognition. It serves as a benchmark for developing and validating fault diagnosis algorithms for rotating machinery, particularly for evaluating model performance under varying operating conditions.

Institutions

• Guilin University of Electronic Technology

  Guangxi, Guilin

Categories

Funders

• Natural Science Foundation of China

  Grant ID: 42263003
• Guangxi Science and Technology Base and Specialized Talents

  Grant ID: 2021AC19451
• Guiding the Local Science and Technology of China

  Grant ID: ZY24212015

Licence