陆路交通关键大型构造物服役能力感-联-知-融-判一体化智能平台研发数据集

构建了多维度科学数据集，具体涵盖以下类型数据：空间信息数据方面，采用无人机平台获取的桥梁裂缝精细化巡检数据及三维实景模型数据，结合沥青路面三维激光扫描病害数据与探地雷达内部损伤数据，为建立多源大数据机器学习的数据-模型融合方法提供数字底座；结构状态数据方面，整合桥梁全生命周期服役过程中的定期检测数据（外观/专项检查）、结构健康监测系统采集的长期性能指标数据，以及无砟轨道隐蔽病害弹性波、超声波阵列检测数据，为陆路交通大型构造物服役状态全生命周期数据库建设提供了良好支撑；智能预警数据方面，桥梁防船撞实时监测数据与风致振动响应数据，为构建基于机器学习的结构服役能力智能研判与预警平台提供关键数据验证集。该数据体系通过多模态数据融合，有效支撑了陆路交通关键大型构造物服役能力智能测试装备与平台的研发。
数据集的内容：包括了对崇启大桥主桥通航孔暗光、正常光条件下的船舶影像数据，检测距离在400~500m之间，数据类型为.jpg。江阴大桥主桥主梁竖向振动的监测数据。
数据类型：JPG/DC。
采集方案：通过查阅国内外桥梁主动防船撞监测的相关文献和标准，设计了基于视频的桥梁主动防船撞监测方案，征求了国内行业领域内专家意见并通过了专家组评审。以崇启大桥主桥为对象，在主桥钢箱梁3#、4#、5#墩桥面护栏上安装3台自主研发的船撞感知预警设备，采集主桥通航孔船舶影像，监测环境包括暗光和正常光。
采集地点：崇启大桥，江阴大桥
采集时间：2022年1月－2022年12月；2023年1月－2023年12月
设备情况：自主研发的船撞感知预警设备；单向加速度传感器。

A multi-dimensional scientific dataset was constructed, covering the following types of data:
1. Spatial information data: Fine-grained inspection data of bridge cracks and 3D reality model data collected via unmanned aerial vehicle (UAV) platforms, combined with 3D laser scanning defect data of asphalt pavement and internal damage data from ground-penetrating radar (GPR), providing a digital foundation for establishing data-model fusion methods for multi-source big data machine learning.
2. Structural state data: Integrated regular inspection data (appearance/special inspection) during the full-life cycle service process of bridges, long-term performance index data collected by structural health monitoring (SHM) systems, and elastic wave and ultrasonic array detection data of hidden defects in ballastless tracks, providing strong support for the construction of full-life cycle databases for the service status of large-scale land transportation structures.
3. Intelligent early warning data: Real-time monitoring data of bridge anti-collision with ships and wind-induced vibration response data, providing a key data validation set for constructing an intelligent judgment and early warning platform for structural service capacity based on machine learning.
This data system, through multimodal data fusion, effectively supports the research and development of intelligent testing equipment and platforms for the service capacity of key large-scale land transportation structures.

### Dataset Content
It includes ship image data collected at the navigation channels of the main bridge of Chongqi Bridge under low-light and normal light conditions, with a detection distance ranging from 400 to 500 meters, and the data format is .jpg. It also covers monitoring data of vertical vibration of the main girder of the main bridge of Jiangyin Bridge.

### Data Types
JPG/DC

### Collection Scheme
By reviewing relevant domestic and international literature and standards on active bridge anti-collision monitoring, a video-based active bridge anti-collision monitoring scheme was designed. The scheme was solicited for opinions from domestic industry experts and passed the review of the expert panel. Taking the main bridge of Chongqi Bridge as the research object, three self-developed ship collision perception and early warning devices were installed on the bridge deck guardrails of piers 3#, 4#, and 5# of the main bridge's steel box girder, to collect ship images at the navigation channel of the main bridge, with monitoring environments including low-light and normal light conditions.

### Collection Locations
Chongqi Bridge, Jiangyin Bridge

### Collection Period
January 2022 – December 2022; January 2023 – December 2023

### Equipment Specifications
Self-developed ship collision perception and early warning equipment; unidirectional acceleration sensors.

搜集汇总

背景与挑战

背景概述

该数据集服务于陆路交通关键大型构造物服役能力智能平台的研发，整合了多源异构数据，包括桥梁裂缝巡检、三维模型、结构健康监测和防船撞预警等空间信息、状态数据和智能预警数据。具体涵盖崇启大桥和江阴大桥在2022年至2023年采集的船舶影像及主梁振动监测数据，通过多模态融合支撑智能测试装备开发。