江苏水利Issue(1)：68-72,5.
皂河泵站设备状态监测及智能化故障诊断系统探究
Research on equipment status monitoring and intelligent fault diagnosis system for Zaohe Pump Station
孙宇 1王浩男 1刘海艳1
作者信息
- 1. 江苏省骆运水利工程管理处,江苏 宿迁 223800
- 折叠
摘要
Abstract
Based on the intelligent requirements of pump station operation and maintenance,combined with deep learning models and the actual situation of Zaohe Pump Station,a pump unit equipment status monitoring and fault diagnosis framework coupled with multi-source data was constructed.A variety of sensors were deployed on pumping station units for data collection,and a CNN-LSTM model was constructed accordingly for equipment fault diagnosis in this study.The research results show that CNN-LSTM model can identify six typical faults of pump station units,and the performance of the CNN-LSTM model is superior to that of single CNN and SVM models,which can provide effective technical support for the operation and maintenance decision-making of pump stations.关键词
设备监测/故障分析/智能化模型/皂河泵站Key words
equipment monitoring/fault diagnosis/intelligent model/Zaohe Pump Station分类
建筑与水利引用本文复制引用
孙宇,王浩男,刘海艳..皂河泵站设备状态监测及智能化故障诊断系统探究[J].江苏水利,2026,(1):68-72,5.
