基于隐含病害的道路性能预测及维修方案决策优化方法
By constructing a pavement PCI prediction model using three-dimensional ground-penetrating radar detection and multi-objective optimization algorithms, the problem of neglecting hidden defects in pavement maintenance is solved, enabling refined evaluation of pavement performance and optimization of maintenance plans, thereby improving prediction accuracy and maintenance effectiveness.
CN121352187BActive Publication Date: 2026-07-17EAST CHINA JIAOTONG UNIVERSITY
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- EAST CHINA JIAOTONG UNIVERSITY
- Filing Date
- 2025-08-27
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
Existing technologies neglect the development of hidden defects in road maintenance decisions, resulting in unsustainable maintenance effects, rapid re-damage of the road surface after maintenance, and low efficiency in the use of maintenance funds.
Method used
Based on the hidden defects data detected by 3D ground-penetrating radar, and combined with decision tree algorithm and multi-objective optimization algorithm, a road PCI prediction model is constructed to optimize the road maintenance plan in order to maximize the future PCI or minimize the cost.
Benefits of technology
This improved the accuracy of road performance prediction and the scientific nature of maintenance plans, ensuring the sustainability of maintenance results and the efficiency of fund utilization.
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Figure CN121352187B_ABST
Abstract
本发明提供一种基于隐含病害的道路性能预测及维修方案决策优化方法，涉及路面养护决策优化技术领域，所述方法步骤包括采集各养护单元的表面病害数据参量和隐含病害数据参量；计算各养护单元的当前路面PCI值；运用决策树算法对隐含病害按类型、顶端深度位置和底端深度位置进行分类；基于分类结果构建自然衰变和不同处治深度的路面PCI预测模型；利用路面PCI预测模型计算各养护单元在不同处治方式下的PCI预测值，以及各养护单元在不同处治深度对应的PCI增幅效益和预算成本；采用DE算法结合NSGA‑II算法的多目标优化算法构建路面维修技术方案决策优化模型，以养护效益最大化和养护成本最小化为双目标进行路面维修技术方案决策寻优计算，并依据TOPSIS法输出最优方案。
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