摘要
为实现大跨度预应力混凝土桥拆除的安全可控,通过分析桥梁拆除的特点及存在的技术问题,明确了基于数字孪生体技术的桥梁智能拆除的概念,厘清了桥梁智能拆除技术的发展阶段,展望了基于数字孪生体技术的桥梁智能拆除应用前景,综述了数字孪生体技术在桥梁工程中的研究现状;结合某大桥拆除工程案例,对数字孪生体技术进行探索应用,不断提高桥梁拆除过程内力状态预测和控制精度,避免再利用构件二次损伤。研究结果表明:大跨度预应力混凝土桥拆除具有恒载内力状态不确定和施工状态不可控的特点,拆除时的结构力学行为是一个瞬间释放的过程,当主梁恒载负弯矩无法匹配预应力提供的正弯矩时,墩梁结合处梁段存在底板拉裂和顶板压溃的风险;服役桥梁在荷载和环境长期耦合作用下结构性能不断劣化,由于养护不到位导致桥梁过早进入病害高发期,迫切需要通过养护加固提升结构性能,但是“过度医疗”的桥梁结构在经过长期运营后结构性能劣化速率会不断加快,将大大缩短桥梁的使用寿命,因此在最佳的养护时机采取合适的养护措施可以有效延长桥梁使用寿命;然而,一系列维修加固措施又会使得桥梁结构状态精准评估和预测愈发困难;桥梁智能拆除是借助新一代信息技术,实时掌握桥梁拆除全过程的真实受力状态,通过数据驱动虚拟桥梁在拆除过程中进行自感知、自演化、自学习、自评估、自决策和自执行,逐步实现人机协同拆除、自动化智能拆除的施工创新模式;借助三维激光扫描仪和全站仪对桥梁结构进行数字重构,精准掌握桥梁恒载分布状况及拆除梁段吊重,通过状态反演的方法对拆除前外观病害和拆除中结构响应进行状态验证和模型修正,明确病害成因及演化规律,掌握结构恒载内力状态,动态调整监控阈值逐步逼近桥梁真实应力状态,从而预先识别风险工况并采取积极高效的安全控制措施,实现桥梁拆除过程的精准预测和控制;对桥梁拆除后再利用构件进行精确测量、有损检测、耐久性试验和长期性能实时监测,有助于提高数字化检测技术的测量精度和效率,推动桥梁结构长期性能演化规律研究;基于数字孪生体技术的桥梁智能拆除研究方向应重点关注桥梁损伤构件无损检测技术及定量分析方法、桥梁结构病害和长期性能演化规律、既有损伤的桥梁结构精细化模拟仿真技术、基于物联网技术的桥梁智能监测系统、基于数据驱动的智能拆除机器人自动化施工技术和桥梁全生命周期内数字模型构建、使用、维护、管理体系。
In order to achieve the safety and controllability of the demolition of long-span prestressed concrete bridges, the concept of intelligent bridge demolition based on digital twin technology was made clear by analyzing the characteristics and existing technical problems of bridge demolition. The development stage of intelligent bridge demolition technology was clarified. The application prospects of intelligent bridge demolition based on digital twin technology were forecasted and the research status of digital twin technology in bridge engineering was reviewed. Combined with a bridge demolition project, the internal force state prediction and control accuracy of bridge demolition process were continuously improved to avoid the secondary damage of reuse components through the exploration and application of digital twin technology. The results show that the demolition of long-span prestressed concrete bridges has the characteristics of uncertain internal force state under dead load and uncontrollable construction state. The structural mechanical behavior is an instantaneous release process during the demolition. When the dead load bending moment of the main beam can not match the positive bending moment provided by the prestress, there is a risk of floor cracking and roof collapse at the beam section of the pier-beam junction. The structural performance of the service bridge continues to deteriorate under the long-term coupling effect of load and environment. Due to the insufficient maintenance, the bridge enters the period of high disease incidence prematurely, and it is urgent to maintain and strengthen to improve the structural performance. However, the degradation rate of structural performance of overtreatment bridge structure will continue to accelerate after long-term operation, which will greatly shorten the service life of the bridge. Therefore, taking appropriate maintenance measures at the best maintenance time can effectively prolong the service life of the bridge. However, a series of maintenance and reinforcement measures will make accurate assessment and prediction of bridge structure more difficult. With the help of a new generation of information technology, intelligent bridge demolition can grasp the real stress state of the whole process of bridge demolition in real time. Through data-driven virtual bridge in the demolition process, self-perception, self-evolution, self-learning, self-assessment, self-decision-making and self-execution are carried out, and the construction innovation mode of man-machine collaborative demolition and automatic intelligent demolition is gradually realized. With the help of three-dimensional laser scanner and electronic total station, the digital reconstruction of the bridge structure is carried out to accurately grasp the dead load distribution of the bridge and the weight of the removed beam section. Through the state inversion method, the state verification and model correction of the appearance disease before the demolition and the structural response during the demolition are carried out. The cause and evolution law of the disease are clarified, the internal force state of the structure under dead load is mastered, and the monitoring threshold is dynamically adjusted to gradually approach the real stress state of the bridge, so as to identify the risk conditions in advance and take active and efficient safety control measures to realize the accurate prediction and control of the bridge demolition process. Accurate measurement, damage detection, durability test and long-term performance real-time monitoring of reusable components after bridge demolition are helpful to improve the measurement accuracy and efficiency of digital detection technology and promote the study of long-term performance evolution law of bridge structures. The research direction of bridge intelligent demolition based on digital twin technology should focus on the research of nondestructive testing technology and quantitative analysis method of bridge damage components, bridge structure disease and long-term performance evolution law, fine simulation technology of existing damaged bridge structure, bridge intelligent monitoring system based on internet of things technology, automatic construction technology of intelligent demolition robot based on data-driven and digital model construction, use, maintenance and management system in the whole life cycle of bridge.
作者
刘永健
唐志伟
肖军
刘江
龚勃旭
王壮
LIU Yong-jian;TANG Zhi-wei;XIAO Jun;LIU Jiang;GONG Bo-xu;WANG Zhuang(School of Highway,Chang an University,Xi'an 710064,Shaanxi,China;Research Center of Highway Large Structure Engineering on Safety,Ministry of Education,Chang an University,Xi'an 710064,Shaanxi,China;Shaanxi Province“Four Bodies-One Union”College-Enterprise Union Research Center of Bridge Engineering Intelligent Construction Technology,Xi'an 710199,Shaanxi,China;Engineering Design and Research Institute of CCCC Second Highway Engineering Bureau Co.,Ltd,Xi'an 710199,Shaanxi,China)
出处
《建筑科学与工程学报》
CAS
北大核心
2022年第4期1-23,共23页
Journal of Architecture and Civil Engineering
基金
陕西省交通运输厅科研项目(21-43K)
中交二公局重点研发课题(2020X-2-6)。
关键词
大跨度预应力混凝土桥
智能拆除
全生命周期
状态评估
数字孪生体
新一代信息技术
long-span prestressed concrete bridge
intelligent demolition
life cycle
condition assessment
digital twin
new generation of information technology
