中国民航大学学报 ›› 2024, Vol. 42 ›› Issue (2): 51-57.

• 未来机场及智能装备 • 上一篇    下一篇

机坪泛光照明环境仿真与组合机位照明分析

  

  1. 1. 中国民航大学交通科学与工程学院, 天津 300300;2. 太原国际机场有限责任公司, 太原 030032
  • 收稿日期:2023-07-12 修回日期:2023-09-20 出版日期:2024-12-19 发布日期:2026-08-03
  • 基金资助:
    天津市研究生科研创新项目(2022SKYZ248);太原武宿国际机场科技研发项目(H01420210340)

Simulation of apron floodlight environment and illuminance analysis of combined aircraft stands

  1. 1. College of Transportation Science and Engineering, CAUC, Tianjin 300300, China; 2. Taiyuan International Airport Co., Ltd., Taiyuan 030032, China
  • Received:2023-07-12 Revised:2023-09-20 Online:2024-12-19 Published:2026-08-03

摘要:  机坪泛光照明系统(AFS,apron floodlight system)是建设绿色机场和节约能耗的重要环节,但对机坪泛光照 明环境精细化分析的不足限制了照明节能的策略优化。 对此,本文采用 DIALux evo 平台建立组合机位照 度仿真模型,提出基于机坪运行功能的分区照明评价指标,对前列式与转角式组合机位开展参数影响分 析。 结果表明:对 C 类停机位需通过双侧高杆灯照明以满足基本照度条件,飞机和廊桥对光线的遮蔽影响不 容忽视;转角式组合机位由于照明范围大需控制灯具垂直俯仰角投射方向,当垂直俯仰角大于 45°时容易 导致眩光指标超出限值,对保障驾驶舱安全性和客舱舒适度较为不利。 通过与神经网络算法融合,可进一 步完善高杆灯照明参数优化过程。

关键词: 泛光照明, 组合机位, 照度仿真, 眩光

Abstract: Apron floodlight system (AFS) is vital for green airport development and energy saving, while the lack of detailed analysis of the apron floodlighting environment limits the strategy optimization of lighting energy saving. In this regard, an illuminance simulation model of combined aircraft stands is established using DIALux evo platform, a zoning lighting evaluation index based on apron operation function is proposed, and parameter impact analysis is carried out for both front and corner combined aircraft stands. Research results indicate that dual side high mast is necessary for the basic illuminance requirement of C-class aircraft stand, and the shading effect of aircraft and corridor bridge on light cannot be ignored. As for the corner combined aircraft stands, due to the large lighting range, it is necessary to control the vertical pitch angle projection direction of the lighting fixtures, and when the vertical pitch angle is greater than 45 °, it is easy to cause glare indicators exceeding the limit, which is not conducive to ensure cockpit safety and cabin comfort. By integrating with neural network algorithm, the optimization process of high mast lighting parameters can be further improved.

Key words: floodlight, combined aircraft stands, illuminance simulation, glare

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