工业设备故障诊断评测数据集

本数据集聚焦工业旋转设备故障诊断算法评测，覆盖滚动轴承、齿轮箱、电机、离心泵、风机等设备类型。数据内容包括设备元数据、工况参数（转速、负载）、多通道时域信号（振动、电流、温度等，采样频率12kHz~50kHz）、故障标签（健康状态、故障类型、严重等级）及统一的训练/测试划分。适用于故障诊断模型训练、跨工况迁移学习、少样本学习、算法对比评测及预测性维护系统开发等场景。This dataset focuses on the evaluation of fault diagnosis algorithms for industrial rotating equipment, covering equipment types such as rolling bearings, gearboxes, electric motors, centrifugal pumps, and fans. Its data content includes equipment metadata, operating condition parameters (rotational speed, load), multi-channel time-domain signals (vibration, current, temperature, etc., with sampling frequencies ranging from 12 kHz to 50 kHz), fault labels (health status, fault type, severity level), and unified training/testing splits. It is applicable to scenarios such as fault diagnosis model training, cross-condition transfer learning, few-shot learning, algorithm comparative evaluation, and predictive maintenance system development.

搜集汇总

背景与挑战

背景概述

该数据集专注于工业旋转设备的故障诊断算法评估，涵盖滚动轴承、齿轮箱、电机等多种设备类型，提供包含设备元数据、工况参数、多通道时域信号及故障标签的标注数据。它适用于模型训练、跨工况迁移学习、算法对比及预测性维护系统开发等场景。