基于监测数据预测的桥梁长周期养护模式研究

Study on Long-term Maintenance Mode of Bridges Based on Monitoring Data Prediction

摘要:

针对北方寒冷地区老旧桥梁病害复合化、结构恶化、养护成本激增的问题，突破传统短期碎片化养护局限，提出系统性长周期养护方案。基于2023—2025年白城市58座国省干线桥梁、151座涵洞的三位一体监测数据，构建回代误差不大于5%的线性回归预测模型，设计“数据驱动—智慧赋能—全链整合—场景适配—绩效导向”的长周期养护模式，并从技术、经济、操作三方面论证可行性。该模式通过差异化监测、系统性处置、绩效化考核协同运作，可实现病害处置合格率不小于98%，单位桥长年养护成本降17.1%，跨铁路养护协调耗时缩53.3%；2028年复合性病害发生率从96.6%降至40%，结构性裂缝发生率降至25%以下，可为北方寒冷地区同类桥梁养护提供技术框架与管理范式。

Abstract:

Aiming at the problems of disease compounding, structural deterioration and surging maintenance costs of old bridges in cold northern China, the limitations of traditional short-term fragmented maintenance is broken through and a systematic long-term maintenance scheme is proposed. Based on the trinity monitoring data of 58 national and provincial highway bridges and 151 culverts in Baicheng City from 2023 to 2025, a linear regression prediction model with back-substitution error ≤ 5% is constructed, and a long-term maintenance mode featuring “data-driven, smart empowerment, full-chain integration, scenario adaptation and performance orientation” is designed. And its feasibility is demonstrated from three aspects of technology, economy and operation. Through the coordinated operation of differentiated monitoring, systematic disposal and performance-based assessment, the mode can achieve a disease disposal qualification rate ≥ 98%, a 17.1% reduction in annual maintenance cost per unit bridge length and a 53.3% reduction in cross-railway maintenance coordination time. In 2028, the incidence of composite diseases will drop from 96.6% to 40%, and the incidence of structural cracks to below 25%, which can provide a technical framework and management paradigm for the maintenance of similar bridges in cold northern China.