基于OPC控制网络协议多维度异构故障数据集

该数据集利用多种传感器在试验台上获取各类旋转机械典型故障数据，包括振动、声等多类型工况数据，具体采用基于事件触发型实现海量数据采集，工艺过程数据仅采集变化时刻的数据，机泵振动数据采用事件触发采集，以通过最优的数据采集策略实现关键数据点捕捉，过滤重复数据，实现高效采集和最小化存储，支持事件触发型的多维度异构复合分布数据采集和负载调节。

This dataset acquires typical fault data of various rotating machinery and multi-type operating condition data including vibration and acoustic signals via multiple sensors installed on a test bench. It specifically employs an event-triggered mechanism for massive data collection: process data only collects data at moments when process variables change, while vibration data of pumps and motors is collected using the event-triggered strategy as well. This design aims to capture key data points, filter redundant data, enable efficient collection and minimize storage through an optimal data acquisition strategy, and supports event-triggered multi-dimensional heterogeneous composite distributed data collection and load adjustment.

搜集汇总

背景与挑战

背景概述

该数据集是针对旋转机械故障诊断的，通过多种传感器采集振动、声等多维度异构故障数据，采用事件触发型策略实现高效采集和存储优化。它基于OPC控制网络协议，支持智能工厂工业互联网系统的研究，属于国家重点研发计划项目的一部分。