Sound Datasets of a Rolling Element Bearing under Various Operating Conditions

Welcome to the FSTF Mechanical Laboratory at Sidi Mohamed Ben Abdellah University. Within this repository, we present a comprehensive collection of ball-bearing test data encompassing both normal and faulty bearings across diffrent operating speeds. The experimental procedures were conducted utilizing a specialized test rig rotor system, with sound data meticulously measured at proximal and distal locations relative to the housing bearings. These web pages serve as a unique resource, meticulously documenting the precise test conditions of the motor and detailing the bearing fault status for each conducted experiment. The datasets are bifurcated into two distinct categories: the first category entails recordings obtained using a stethoscope, denoted as datasets 1, while the second category comprises recordings conducted without a stethoscope under diffrent operating conditions, referred to as datasets 2. In both cases, bearings—specifically SKF model 6004, grooved ball bearings—were installed in a rotor system specified in Appendix A, as provided by the Gunt Company [1]. The defective bearings featured artificial damage in the inner race, outer race, and ball element, representing localized defects, as well as a bearing afflicted with a looseness defect due to prolonged operation. Data acquisition procedures involved the recording of sound signals emanating from the bearings under diverse conditions, employing a mobile application named VibroTeak, developed by our team. This application facilitates the recording of sound signals in (.wav) format at a sampling rate of 44.1 kHz. Subsequently, the sound data was imported into Matlab using the "audioread" function for further processing. Figure 1 (Appendix A) illustrates the acquisition of acoustic signals utilizing a stethoscope connected to a smartphone via the jack input. The datasets presented herein offer a novel avenue for researchers to delve into, assess, and propose innovative diagnostic algorithms tailored to this specific type of data. References: [1] Gunt, “PT 500.12 Roller bearing faults kit.” https://www.gunt.de/en/products/mechatronics/machinery-diagnosis/roller-bearing-faults-kit/052.50012/pt500-12/glct-1:pa-148:ca-77:pr-1030.欢迎来到西迪·穆罕默德·本·阿卜杜拉大学（Sidi Mohamed Ben Abdellah University）FSTF机械实验室。本仓库提供一套全面的球轴承测试数据集，涵盖不同运行转速下的正常轴承与故障轴承数据。实验采用专用试验台转子系统开展，在轴承座的近端与远端位置精准采集声学数据。本网页作为独特的研究资源，详尽记录了每次实验的电机精确测试条件，以及对应轴承的故障状态。 本数据集分为两个类别：第一类为使用听诊器采集的数据集（记为数据集1）；第二类为未使用听诊器、在不同运行工况下采集的数据集（记为数据集2）。两类实验均采用SKF品牌6004型沟型球轴承，安装于附录A指定的转子系统中，该转子系统由Gunt公司提供[1]。故障轴承包含内圈、外圈与滚动体的人工局部损伤缺陷，以及因长期运行导致的松动缺陷。 数据采集环节使用团队自研的名为VibroTeak的移动应用程序，采集轴承发出的声音信号，采样率为44.1 kHz，保存格式为(.wav)。后续通过Matlab的"audioread"函数导入声学数据以开展后续处理。图1（附录A）展示了通过耳机插孔将听诊器连接至智能手机以采集声学信号的过程。 本数据集为研究人员提供了全新的研究路径，可用于开发、评估并提出针对该类特定数据的创新诊断算法。 参考文献：[1] Gunt公司，“PT 500.12 滚动轴承故障套件”，https://www.gunt.de/en/products/mechatronics/machinery-diagnosis/roller-bearing-faults-kit/052.50012/pt500-12/glct-1:pa-148:ca-77:pr-1030.

搜集汇总

背景与挑战

背景概述

该数据集由FSTF机械实验室提供，专注于滚动轴承（SKF 6004型号）在不同运行条件下的声音采集，包含正常状态及多种故障类型（如内圈、外圈、球体缺陷和松动）的数据。数据分为使用听诊器和不用听诊器两类，通过VibroTeak应用以44.1 kHz采样率记录为.wav格式，旨在支持轴承故障诊断算法的研究与开发。