车体涂层质量自动检测测试数据

该数据集主要面向高铁白车身涂装全流程机器人自动化生产线中的自动喷涂工艺技术研究、自动喷涂质量检测及车体涂层特性评价等需求建设。为检测车体表面油漆自动喷涂质量，依据国家标准GB/T 5226.1-2019《机械电气安全机械电气设备第1部分：通用技术条件》与GB/T 38762.1-2020《产品几何技术规范（GPS）尺寸公差 第1部分：线性尺寸》，对轨道车辆车体涂层厚度测量误差、光泽度测量重复性、色差检测重复性及表面缺陷进行系统测量与评价。数据于2025年10月23日至24日采集于中车青岛四方机车车辆股份有限公司，由湖北机电院机械产品质量检测中心工程师完成测试流程、数据采集、处理及汇总，总数据量为2.45 GB。采集过程中，使用EXR50-1900机器人搭载TIME2600涂层测厚仪、CS-380光泽度仪、CRX-66色差仪及MV-CS050-10UC工业相机对车体表面涂层进行多维度测量。数据采集覆盖车体表面底漆及中涂漆面漆区域，记录涂层厚度、光泽度、色差及表面缺陷信息，并生成对应测量报告。数据集内容包括涂层厚度测量误差、光泽度测量重复性、色差检测重复性，以及车体涂层表面自动检测图片140张、测量数据表格。同时还包含缺陷对应图像、图像预处理后的检测结果及机器人末端位置等信息，可用于涂装工艺评估、喷涂质量控制及自动化检测算法验证。该数据集可用于支持验证涂层厚度测量误差≤±2%、光泽度测量重复性≤±0.2GU、色差检测重复性≤0.05的技术指标，为高铁白车身涂装全流程的质量控制与工程优化提供标准化、可复用的数据资源。数据量为2.45GB。This dataset was constructed to address the needs of automatic spraying process research, automated spraying quality inspection, and carbody coating property evaluation in the fully automated robotic painting production line for high-speed railway body-in-white. To detect the automatic spraying quality of carbody surfaces, systematic measurement and evaluation were conducted on coating thickness measurement error, gloss measurement repeatability, color difference detection repeatability, and surface defects of rail vehicle carbodies, in accordance with Chinese national standards GB/T 5226.1-2019 "Safety of machinery, electrical equipment for machinery – Part 1: General technical requirements" and GB/T 38762.1-2020 "Geometrical product specifications (GPS) – Dimension tolerances – Part 1: Linear dimensions". The data was collected from CRRC Qingdao Sifang Rolling Stock Co., Ltd. between October 23 and 24, 2025. The testing procedures, data collection, processing, and aggregation were completed by engineers from the Hubei Institute of Mechanical and Electrical Engineering Mechanical Product Quality Inspection Center, with a total data volume of 2.45 GB. During data collection, an EXR50-1900 robot equipped with a TIME2600 coating thickness gauge, CS-380 gloss meter, CRX-66 colorimeter, and MV-CS050-10UC industrial camera was used to perform multi-dimensional measurements on the carbody surface coatings. The data collection covers the primer, intermediate coat, and top coat areas of the carbody surface, recording information such as coating thickness, glossiness, color difference, and surface defects, and generating corresponding measurement reports. The dataset includes coating thickness measurement errors, gloss measurement repeatability, color difference detection repeatability, 140 automatically captured images of carbody coating surfaces, and measurement data tables. It also contains defect-corresponding images, detection results after image preprocessing, robot end position information, and other data, which can be used for coating process evaluation, spraying quality control, and automated detection algorithm validation. This dataset can be used to support the validation of technical indicators including coating thickness measurement error ≤ ±2%, gloss measurement repeatability ≤ ±0.2 GU, and color difference detection repeatability ≤ 0.05. It provides standardized and reusable data resources for quality control and engineering optimization of the entire high-speed railway body-in-white painting process. The total data volume is 2.45 GB.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于高铁白车身涂装全流程的机器人自动化生产线，用于自动喷涂工艺研究、质量检测及涂层特性评价。它包含车体涂层厚度、光泽度、色差和表面缺陷的系统测量数据，采集于2025年10月，总数据量为2.45GB，可用于验证技术指标和支持涂装质量控制与算法验证。