青岛港自动化码头关键设备数据优化和健康诊断数据集

数据主要由AGV三个系统采集而构成：导航系统、电控系统和液压系统。其中，导航系统主要负责通过安装在车体前后两端的RFID天线、安装于车桥位置的4个轮速编码器、安装于4个车轮转轴的角度编码器、陀螺仪、安装于车头和车尾的平面激光传感器等获得如下152个传感器信号数据信号。针对AGV，每一组数据的原始标签都是按照青岛港自动化码头技术工程师标定的故障原因给定的基础上，在数据分析的过程中发现，AGV设备出现的异常状态种类繁多而且多数的异常状态比较相似，对原始数据处理后进行重新归类。The dataset is mainly collected from three systems of AGV: navigation system, electronic control system and hydraulic system. Specifically, the navigation system is responsible for acquiring 152 sensor signals via various sensors including RFID antennas installed at the front and rear ends of the vehicle body, four wheel speed encoders mounted on the axle positions, angle encoders installed on the shafts of the four wheels, gyroscopes, and planar laser sensors installed at the front and rear ends of the vehicle, etc. For each AGV dataset, the original labels were initially assigned based on the fault reasons calibrated by technical engineers at the automated terminal of Qingdao Port. However, during the data analysis process, it was found that there are a wide variety of abnormal states of AGV equipment, and most of these abnormal states are relatively similar. Therefore, the original data was processed and reclassified.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于青岛港自动化码头AGV关键设备的传感器数据，涵盖导航、电控和液压系统采集的152个信号，数据量达15.7GB，旨在支持设备异常检测和健康诊断研究。数据经过优化处理，原始故障标签被重新归类以应对复杂异常状态，适用于计算机科学技术和交通运输工程领域的分析应用，属于国家重点研发计划项目的一部分。