A municipal drainage engineering whole-cycle cost dynamic management method based on BIM and internet of things

CN121365947BActive Publication Date: 2026-08-28盐城市城镇排水管理处
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Patent Information

Application Number
CN202511534995.4
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-10-24
Publication Date
2026-08-28
Estimated Expiration
2045-10-24

AI Technical Summary

Technical Problem

[0005]为了克服现有技术的不足，本发明的目的是提供一种基于BIM与物联网的市政排水工程全周期造价动态管理方法，本发明解决了现有技术中无法将BIM与物联网数据在统一编码下实现稳定、实时、可追溯的关联与闭环控制，致使工程量与成本难以动态计量、偏差难以及时量化和纠偏，无法实现全周期动态造价管理的问题

Benefits of technology

[0057]本发明提供了一种基于BIM与物联网的市政排水工程全周期造价动态管理方法，包括：在统一编码体系下构建工程对象的BIM 5D模型，所述BIM 5D模型用于完成WBS/CBS/BOQ关联与初始进度计划编制，并基于价格数据库与指数库生成目标成本与造价基线，其中，所述工程对象包括：管网、检查井、泵站；根据BIM 5D模型并利用物联网设备采集对应的现场数据并进行标准化处理，得到标准化时序数据集；根据所述标准化时序数据集与天气工况信息对物联网设备监测精度进行动态评估，以识别极端天气触发条件并计算设备健康度与数据可信度，对异常漂移、缺失与噪声进行标注，得到带有可信度标签的标准化时序数据集；基于所述可信度标签构建冗余数据融合与权重修正机制，对同类量测的多源数据进行加权融合与模型校准，输出置信度增强的标准化时序数据集；根据所述置信度增强的标准化时序数据集和所述目标成本与造价基线进行动态计算，得到动态计量结果，所述动态计量结果包括实际工程量、资源实耗；利用所述动态计量结果对所述BIM 5D模型进行进度更新，得到更新后的BIM 5D模型；基于更新后的BIM 5D模型，按合同与清单计价规则进行期间与累计造价滚动计算，得到偏差指标并根据所述偏差指标和预设的绩效对计划值与实际值进行量化比较，得到造价偏差、进度偏差与完工预测值；根据所述造价偏差、进度偏差、完工预测值并结合关键驱动因子构建预测模型并根据所述预测模型得到风险预测结果；根据所述风险预测结果生成对应的控制措施集；根据所述控制措施集对所述目标成本与造价基线进行优化，得到优化后的结果并用于下一周期的造价管理。本发明在统一编码体系下以BIM 5D为数据与规则的主线，将WBS/CBS/BOQ、初始进度计划与目标成本/造价基线一体化建立，通过物联网现场数据的标准化、可信度评估与冗余融合，显著提升多源量测的可靠性与可用性；基于置信度增强的时序数据对实际工程量与资源实耗进行动态计量，并将结果实时写回BIM 5D以联动更新进度，实现由客观量测驱动的进度与造价同步管控；在合同与清单规则下开展期间与累计造价滚动计算，形成可审计的造价与进度偏差，以及面向完工的预测值；进一步利用偏差与关键驱动因子构建预测模型，输出风险预测结果并生成对应控制措施集，再将措施闭环到目标成本与造价基线的周期性优化，从而实现“数据—计量—进度—造价—风险—控制—优化”的闭环，减少异常漂移、缺失与噪声对决策的干扰，提升偏差识别的及时性、风险预判的前瞻性和成本控制的精度与连续性。

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Abstract

The application provides a municipal drainage engineering whole-cycle cost dynamic management method based on BIM and Internet of Things, and relates to the technical field of cost management. It comprises the following steps: completing WBS / CBS / BOQ correlation and initial progress, and forming a target cost baseline based on a price library and an index library. Internet of Things data is collected and standardized, the accuracy and reliability of the equipment are evaluated in combination with the weather, and abnormalities are marked; redundant fusion and weight correction are implemented based on the reliability to generate confidence-enhanced data. The baseline is linked to perform dynamic measurement and progress updating, and the period and cumulative cost are calculated, the cost deviation, progress deviation and completion prediction are quantified, a prediction model is constructed to output risks and generate control measures, the target cost and baseline are optimized, and whole-cycle dynamic cost management is realized.
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