大型地下管网预测性运维多源监测数据融合决策方法

Predictive Operation and Maintenance Decision-Making for Underground Pipelines Based on Fusion of Multi-Source Monitoring Data

摘要:

地下管网是城市和工业能源供给的重要基础设施，建立预测性运维策略是确保其全生命周期内正常服役的关键措施。根据连续式地下管道失效破坏的机理，提出了基于多源监测数据融合的应力分析模型及融合算法。在考虑均匀腐蚀引起的结构退化的基础上，基于时变可靠度提出了地下管网预测性运维检测计划的决策模型。工程实例表明，融合算法可以正确识别并估计通常无法提前预测的纵向弯曲应力和轴向热应力，验证了本文方法的有效性。所提出模型与现有管道可靠度模型对比结果表明，在地下管道安全评价和服役寿命预测中不能忽略纵向弯曲应力的影响。

Abstract:

Underground pipe networks are the critical infrastructures for urban and industrial energy supply. The predictive operation and maintenance （O&M） is the key issue for ensuring service throughout their life cycle. According to the failure damage mechanism of underground continuous pipelines， a stress analysis model is proposed based on the multi-source monitoring data fusion， and specific fusion algorithms are provided. A decision model for the first maintenance inspection plan is presented based on the time-dependent reliability， which considers the structural deterioration caused by uniform corrosion. A practical case showed that the fusion algorithm can successfully estimate unpredictable longitudinal bending stress and axial thermal stress， which demonstrates the effectiveness of the method proposed in this paper. The comparison result between the proposed model and existing model proves that the longitudinal bending stress cannot be ignored in the safety assessment and service life prediction of underground pipelines.