钢铁生产典型故障与异常定位、溯源数据集

钢铁生产典型故障与异常定位、溯源数据集包含了带钢热连轧工艺流程中精轧工艺环节的数据。具体上包括了生产过程中七台精轧机传感器监测数据，精轧过程板坯质量监测数据，生产过程轧制计划数据等信息数据。典型故障数据的采集时间范围是2024年5月1日到2024年5月31日以及2024年7月1日到2024年7月31日，共568个板坯的数据，采样间隔是100ms，包含带钢热连轧过程全流程的精轧设备传感器实时采集数据。异常监测、定位与溯源数据是在热连轧原始数据的基础上，通过云边端协同故障监测与溯源算法生成。包含故障监测特征提取情况，以及故障监测与溯源的结果。A Dataset for Typical Faults, Anomaly Localization and Traceability in Steel Production covers data from the finishing rolling stage of the hot strip rolling production process. Specifically, it includes sensor monitoring data from seven finishing mills during production, slab quality monitoring data during the finishing rolling process, rolling schedule data for the production process, and other relevant information. The collection period for typical fault data spans May 1 to May 31, 2024, and July 1 to July 31, 2024, with a total of 568 slab datasets. The sampling interval is 100 ms, and the dataset also contains real-time sensor data collected from finishing rolling equipment across the entire hot strip rolling production process. The anomaly monitoring, localization and traceability data are generated via cloud-edge-terminal collaborative fault monitoring and traceability algorithms based on the original hot strip rolling data, covering the results of fault monitoring feature extraction and the outcomes of fault monitoring and traceability.

搜集汇总

背景与挑战

背景概述

该数据集聚焦钢铁生产中的故障与异常处理，包含带钢热连轧精轧环节的传感器监测、质量数据和轧制计划信息，覆盖568个板坯的实时采集数据（采样间隔100ms）。其特点在于通过云边端协同算法实现故障监测、定位与溯源，提供故障特征提取和溯源结果，适用于工业过程优化和异常检测研究。