基于大数据分析的基础设施智能化预测性维护研究  

Research on Intelligent Predictive Maintenance of Infrastructure Based on Big Data Analysis

作　　者：杨平 YANG Ping(Ordos Kangbashi District Government Investment Project Construction Center,Ordos,Inner Mongolia,017010,China)

机构地区：[1]鄂尔多斯市康巴什区政府投资项目代建中心,内蒙古鄂尔多斯017010

出　　处：《智能城市应用》2025年第4期104-106,共3页Smart City Application

摘　　要：随着基础设施智能化发展,预测性维护成为提高运行效率和减少故障停机的重要手段。基于大数据分析,通过对基础设施设备运行数据的实时监测与分析,可以及时发现潜在问题并预测设备故障趋势,从而实现精准维护和资源优化配置。大数据技术在维护决策中的应用能够提升基础设施管理的智能化水平,降低维护成本,提高系统稳定性与安全性。研究表明,基于数据驱动的预测性维护模式能够有效延长设备生命周期并提高基础设施整体性能。With the development of intelligent infrastructure,predictive maintenance has become an important means to improve operational efficiency and reduce downtime.Based on big data analysis,real-time monitoring and analysis of infrastructure equipment operation data can timely identify potential problems and predict equipment failure trends,thereby achieving precise maintenance and resource optimization configuration.The application of big data technology in maintenance decision-making can enhance the intelligence level of infrastructure management,reduce maintenance costs,and improve system stability and security.Research has shown that data-driven predictive maintenance models can effectively extend equipment lifecycle and improve overall infrastructure performance.

关 键 词：大数据分析 智能化维护 预测性维护 基础设施管理 设备故障预测 

分 类 号：TM621[电气工程—电力系统及自动化]