涂层机器人自动打磨质量测试数据
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为测试和表征涂层机器人自动打磨质量，本数据集在轨道车辆实际工程背景下构建，重点面向高铁、地铁白车身机器人涂装自动化作业系统中涂层打磨工艺可行性验证、工艺参数优化与质量评估等研究与工程应用需求。数据采集严格依据国家标准 GB/T 1031 2009《产品几何技术规范（GPS） 表面结构 轮廓法 表面粗糙度参数及其数值》和 GB/T 3505 2009《产品几何技术规范（GPS） 表面结构 轮廓法 术语、定义及表面结构参数》，在统一的评价体系下开展自动打磨试验与测量工作。依托无锡中车时代智能装备研究院有限公司搭建的机器人打磨试验平台，在模拟高铁、地铁白车身实际涂装结构和工况条件下，对腻子涂层、中涂漆涂层及面漆涂层开展多组自动打磨试验，通过系统调节打磨压力、轨迹行距、磨盘转速和磨盘移动速度等关键工艺参数，获得不同参数组合下的表面质量响应。试验期间采用符合国标要求的轮廓法测量仪器对打磨后表面粗糙度 Ra 进行测量，并结合涂层厚度变化记录打磨去除量，同时对各组工况下的打磨表面形貌进行图像采集，完整记录磨痕纹理、平整度及光洁度等视觉特征；数据由该单位工程师于 2023 年 5 月 10 日至 2023 年 6 月 30 日按统一技术路线完成采集、整理与汇总，确保了数据来源的工程真实性和过程的可追溯性。形成的数据集覆盖 7 类典型试验场景：包括腻子涂层机器人自动打磨正交试验 16 组、腻子涂层最佳工艺参数验证试验 1 组，中涂漆涂层中分别考察不同轨迹行距、打磨压力、磨盘转速和磨盘移动速度影响的 7+4+3+4 组试验，以及面漆涂层不同打磨压力影响试验 3 组，共计 38 组参数组合，每组均包含完整的工艺参数记录与对应打磨效果图像，用于系统分析打磨参数与表面质量之间的定量关系和定性变化特征。数据总量为 104.76 MB。
This dataset was constructed under the actual engineering background of rail vehicles to test and characterize the automatic grinding quality of coating robots, focusing on the research and engineering application requirements such as coating grinding process feasibility verification, process parameter optimization and quality evaluation in the robotic painting automation operation system of high-speed rail and subway body-in-white. The data collection was strictly conducted in accordance with the national standards GB/T 1031-2009 *Geometrical Product Specifications (GPS) - Surface texture: Profile method - Parameters of surface roughness and their values* and GB/T 3505-2009 *Geometrical Product Specifications (GPS) - Surface texture: Profile method - Vocabulary, definitions and parameters of surface texture*, and automatic grinding tests and measurements were carried out under a unified evaluation system. Relying on the robotic grinding test platform built by Wuxi CRRC Times Intelligent Equipment Research Institute Co., Ltd., multiple sets of automatic grinding tests were conducted on putty coatings, intermediate coatings and topcoat coatings under the conditions simulating the actual painting structure and working conditions of high-speed rail and subway body-in-white. By systematically adjusting key process parameters such as grinding pressure, grinding track spacing, grinding disc rotation speed and grinding disc moving speed, the surface quality responses under different parameter combinations were obtained. During the tests, a profile measuring instrument compliant with national standards was used to measure the surface roughness Ra of the ground surface, and the grinding removal amount was recorded in combination with the change of coating thickness. Meanwhile, images of the ground surface topography under each working condition were collected, and the visual features such as grinding mark texture, flatness and smoothness were fully recorded. The data was collected, sorted and summarized by engineers from this unit from May 10, 2023 to June 30, 2023 following a unified technical route, ensuring the engineering authenticity of the data source and the traceability of the entire process. The formed dataset covers 7 typical test scenarios: 16 sets of orthogonal tests for robotic automatic grinding of putty coatings, 1 set of verification test for optimal process parameters of putty coatings, 7+4+3+4 sets of tests for intermediate coatings investigating the effects of different track spacing, grinding pressure, grinding disc rotation speed and grinding disc moving speed respectively, and 3 sets of tests for topcoat coatings investigating the effect of different grinding pressures, totaling 38 sets of parameter combinations. Each set contains complete process parameter records and corresponding grinding effect images, which are used to systematically analyze the quantitative relationship and qualitative change characteristics between grinding parameters and surface quality. The total data volume is 104.76 MB.
