开展混凝土实时温度监测数据质量分析对于混凝土智能温控具有重要意义。该文提出了一种混凝土实时温度数据移动平均分析方法，将传统移动平均进行了多维度扩展。通过从时间、空间和质量维度对监测数据进行动态求均值，形成用于表征某一时刻、空间点、监测对象的特征温度数据，实现了与混凝土智能温控系统的融合，显著减小了原始监测数据中的系统误差和偶然误差，降低了由于仪器故障、突发状况等造成的数据失真，以及数据误差对计算仿真、分析利用造成的影响。通过白鹤滩、乌东德等大坝混凝土实时温度监测数据的分析应用，结果表明：该方法可提高监控系统的工作性能、数据质量和管理人员的决策能力，为混凝土温控施工与质量评价提供参考。

Real-time temperature monitoring data quality is important for intelligent concrete cooling control. This paper presents a moving-average method for real-time concrete temperature monitoring data which extends the traditional moving average to multiple dimensions including time, space, and quality. Dynamic analyses of the raw data average in the intelligent concrete cooling control system provide temperature data that characterize the conditions at a given moment, spatial location, or object, which significantly reduces the effects of systematic and random errors in the raw data and reduces data distortion caused by instrument failures, sudden environmental changes and other effects. This method then reduces the impact of data errors on subsequent data calculations, simulations, and analyses. Analysis of real-time concrete temperature monitoring data from the Baihetan and Wudongde arch dams shows the advantages of this method for improving the monitoring system, data quality, and decision-making ability of management personnel. The results then provide a reference for concrete temperature control system design and quality evaluations.