Vibration and acoustic data of pitch bearing in wind turbines under time-varying load for fault diagnosis(Cond_3)

Pitch bearing, as the core component of wind turbines, brings the blades to the desired position by adjusting the aerodynamic angle. Due to the harsh working environment of wind turbines, the faults of pitch bearing may lead to the overall failure of wind turbine. However, obtaining the sufficient data of faults for pitch bearings under the actual operating environment is difficult and time-consuming. Thus, a precision-machining mechanical platform of proportionally-scaled pitch bearings was designed and built to simulate its actual operating characteristics. Based on it, the vibration and acoustic data of proportionally-scaled pitch bearings with 11 types of faults under three kinds of loads and two rotational speeds are collected and stored in the sequent data files.
The faults, such as crack, wear and spalling, are artificially created on inner or/and outer ring raceways, as well as rolling body of proportionally-scaled pitch bearings in advance. More especially, single and compound fault data are provided in this dataset.
Ultimately, this dataset provides high-quality data for the studies on fault diagnosis for pitch bearing in wind turbines and rolling bearings with low-speed and heavy loads. It is also employed to validate the effectiveness of newly developed fault diagnosis methods.

变桨轴承（Pitch bearing）作为风力发电机组的核心部件，通过调整气动角度将叶片调整至目标位置。由于风力发电机组的工作环境严苛，变桨轴承发生故障可能引发整机停机故障。然而，在实际运行环境中获取足量的变桨轴承故障数据不仅难度大，且耗时良久。为此，本研究设计并搭建了一套按比例缩放的变桨轴承精密加工机械平台，以模拟其实际运行特性。基于该平台，本数据集采集并存储了11种故障类型的按比例缩放变桨轴承在三种载荷、两种转速下的振动与声学数据，存储于连续数据文件中。
本数据集预先在按比例缩放变桨轴承的内圈、外圈滚道以及滚动体上人工制备了裂纹、磨损、剥落等故障类型。尤为重要的是，本数据集同时包含单故障与复合故障数据。
最终，本数据集可为风力发电机组变桨轴承以及低速重载滚动轴承的故障诊断研究提供高质量数据，同时也可用于验证新型故障诊断方法的有效性。

搜集汇总

背景与挑战

背景概述

该数据集提供了风力发电机变桨轴承在时变负载下的振动和声学数据，包含11种人为制造的故障类型，用于支持故障诊断方法的研究和验证。数据集特别适用于低速重载滚动轴承的故障诊断研究。