铁路货车整车标记智能喷涂技术研究及应用

Research and Application of Intelligent Spraying Technology for Whole Vehicle Markings on Railway Freight Cars

摘要

传统铁路货车整车标记采用人工涂打模式，存在效率低、质量差、安全风险高的行业痛点。本文提出融合多源信息识别、动态自适应控制与轨行式机器人定位的智能喷涂技术方案，搭建双工位节拍化产线，构建感知-决策-执行-监控四层系统架构，攻克多车型适配、墨路稳定、车体变形响应等技术难题。经30天全工况试验验证，该技术单辆车涂打节拍稳定在7分钟，标记不合格品率由8%降至 2%，定位精度达±0.5mm，可覆盖98%主流车型，年直接经济效益115万元，VOC排放降低 99.7%，彻底消除高空作业风险。该技术填补了国内外铁路货车标记自动化节拍化产线的技术空白，达到国际领先水平，为铁路货车造修行业智能化转型提供了可复制的技术范式。

Abstract

Traditional railway freight car marking relies on manual application methods, which suffer from low efficiency, poor quality, and high safety risks-key industry challenges. This paper proposes an intelligent spraying solution integrating multi-source information recognition, dynamic adaptive control, and rail-guided robot positioning. A dual-station rhythmic production line was established, featuring a four-layer system architecture encompassing perception, decision-making, execution, and monitoring, effectively addressing technical hurdles such as compatibility with diverse vehicle models, ink path stability, and response to vehicle deformation. After 30 days of full-condition testing, the technology achieved a stable marking cycle of 7 minutes per vehicle, reduced non-conforming mark rates from 8% to 2%, demonstrated positioning accuracy of ±0.5 mm, covered 98% of mainstream vehicle types, generated annual direct economic benefits of ¥1.15 million, decreased VOC emissions by 99.7%, and completely eliminated aerial work risks. This innovation fills a technological gap in automated rhythmic marking lines for railway freight cars worldwide, reaching internationally leading standards and providing a replicable technical paradigm for the intelligent transformation of the freight car manufacturing and maintenance industry.

关键词

铁路货车 / 标记 / 智能喷涂

Key words

railway freight car / labeling / intelligent spraying

参考文献

[1] 王健， 李刚， 张磊。 铁路货车智能制造技术现状与发展趋势[J]. 中国铁路， 2023, (11): 45-52.

[2] 刘辉， 陈明， 赵亮。 工业机器人在铁路装备制造中的应用[J]. 制造业自动化， 2022, 44 (8): 123-127.

[3] 基恩士 (中国) 有限公司。 激光测距传感器 IL-1000 技术手册[Z]. 2023.

[4] ABB (中国) 有限公司. IRB 1200 防爆机器人技术规格书[Z]. 2023.

[5] 中华人民共和国国家质量监督检验检疫总局. GB/T 9286-1998 色漆和清漆 漆膜的划格试验[S]. 北京： 中国标准出版社， 1998.

[6] 张思民， 王丽， 刘强。 多源信息融合算法在工业检测中的应用[J]. 仪器仪表学报， 2021, 42 (5): 1-10.

[7] 李明， 赵伟， 陈晓。 基于PID算法的机器人动态轨迹控制[J]. 控制工程， 2020, 27 (3): 456-461.