[1]张宇,谈庆敏,杨波,等.面向泵站装备的全息健康管理系统建模及应用[J].江苏水利,2022,(06):35-39.
　ZHANG Yu,TAN Qingmin,YANG Bo,et al.Modeling and application of holographic health management system[J].JIANGSU WATER RESOURCES,2022,(06):35-39.
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面向泵站装备的全息健康管理系统建模及应用()
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《江苏水利》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2022年06期
页码:
35-39
栏目:
水利信息化
出版日期:
2022-07-05

文章信息/Info

Title:
Modeling and application of holographic health management system
文章编号:
1007-7839(2022)06-0035-0005
作者:
张宇1; 谈庆敏2; 杨波1; 张闻裕1; 张瑾1; 蔡廷廷3
（1.江苏省太湖地区水利工程管理处，江苏 苏州 215128；2.江苏航天水力设备有限公司，江苏 扬州 225000；3.华中科技大学机械科学与工程学院，湖北 武汉 430074）
Author(s):
ZHANG Yu1;  TAN Qingmin2;  YANG Bo1;  ZHANG Wenyu1;  ZHANG Jin1;  CAI Tingting3
（1.Water Conservancy Engineering Management Office of Taihu Region of Jiangsu Province, Suzhou 215128, China；2.Jiangsu Aerospace Hydraulic Equipment Co., Ltd., Yangzhou 225000, China；3.School of Mechanical Science and Engineering, Huazhong University of S
关键词:
泵站; 全息数据; 健康管理; 监测
Keywords:
pumping station;  holographic data;  health management;  monitoring
分类号:
TP399
文献标志码:
B
摘要:
为提高泵站装备的运维管理水平，确保泵站安全可靠运行需要，研究提出了一种基于全息数据分析的泵站全息健康管理系统建模方案，开发了相应的系统应用。该系统通过构建统一数据平台实现电流、电压、振动等全息数据的采集、存储与调用，通过搭建统一管理平台实现对泵站装备的管理、分析、可视化交互等功能。在机器学习模型的驱动下，该系统开展对泵站装备的智能化监测与诊断，从而实现对远端装备故障的深度分析、快速反应、及时推送。
Abstract:
To improve the operation and maintenance management of pumping station equipment and ensure the safety and reliability needs of pumping station, a modeling scheme of holographic health management system for pumping stations based on holographic data analysis was proposed. And the corresponding system application was developed. The system realizes the collection, storage and invocation of holographic data such as current, voltage and vibration by building a unified data platform, and realizes the management, analysis and visualization interaction of pumping station equipment by building a unified management platform. Driven by machine learning models, the intelligent monitoring and diagnosis of pumping station equipment were achieved based on holographic data, thus the deep analysis, rapid response and timely pushing for remote equipment failures can be accomplished.

参考文献/References:

[1]崔仕杰，杨立，李俊士. 基于振动和油品在线监测的泵站故障诊断系统[J]. 煤矿机械，2021，42（9）：162-164.
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备注/Memo

备注/Memo:
收稿日期：2022-01-07
作者简介：张宇（1978—），男，高级工程师，本科，主要从事工程管理，智慧泵站建设工作。E-mail:zxnice66@163.com
更新日期/Last Update: 2022-06-15