升压站智能分析与故障预测系统

Intelligent Analysis and Fault Prediction System of Booster Station

文章旨在探讨升压站智能分析与故障预测系统,以提升电力系统稳定性与运行效率。首先,通过先进的数据采集与监测技术,获取升压站设备的实时运行数据,运用数据处理与分析算法,结合人工智能技术,挖掘潜在的故障特征与趋势。其次,选取关键故障特征与指标,构建可靠的故障预测模型,并进行优化。最后,制定实施策略与系统建设,通过应用案例验证模型效果,评估其在升压站运维中的实际应用价值。

The article aims to explore the intelligent analysis and fault prediction system for booster stations,in order to improve the stability and operational efficiency of the power system.Firstly,through advanced data collection and monitoring technology,real-time operational data of the booster station equipment is obtained.Data processing and analysis algorithms are used,combined with artificial intelligence technology,to explore potential fault characteristics and trends.Secondly,select key fault characteristics and indicators,construct a reliable fault prediction model,and optimize it.Finally,develop implementation strategies and system construction,verify the effectiveness of the model through application cases,and evaluate its practical application value in the operation and maintenance of the booster station.