[1]蔡喜昌,冯文嵛,林杰胜,等.大型抽水蓄能电站水轮机组机械振动故障判别模型[J].机械与电子,2024,42(07):64-68.
 CAI Xichang,FENG Wenyu,LIN Jiesheng,et al.Fault Diagnosis Model for Mechanical Vibration of Hydraulic Turbine Units in Large Pumped Storage Power Stations[J].Machinery & Electronics,2024,42(07):64-68.
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大型抽水蓄能电站水轮机组机械振动故障判别模型()
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
42
期数:
2024年07期
页码:
64-68
栏目:
机电一体化
出版日期:
2024-07-26

文章信息/Info

Title:
Fault Diagnosis Model for Mechanical Vibration of Hydraulic Turbine Units in Large Pumped Storage Power Stations
文章编号:
1001-2257 ( 2024 ) 07-0064-05
作者:
蔡喜昌冯文嵛林杰胜林泳骏李东璐
南方电网调峰调频发电有限公司运行分公司,广东 清远 513207
Author(s):
CAI Xichang FENG Wenyu LIN Jiesheng LIN Yongjun LI Donglu
( CSGES Operation Management Branch Company , Qingyuan 513207 , China )
关键词:
大型抽水蓄能电站水轮机组机械振动故障判别信号处理
Keywords:
large pumped storage power station hydraulic turbine unit mechanical vibration fault identification signal processing
分类号:
V743
文献标志码:
A
摘要:
为了提高大型抽水蓄能电站水轮机组机械振动故障判别精度,以及时对其进行维修,保证抽水蓄能电站水轮机组设备安全运行,延长机械使用时长,提出了一种水轮机组机械振动故障判别方法。利用无量纲处理水轮机组机械信号,去除冗余信号,确定振动参数加权分布,设置故障特征量权值,构建抽水蓄能电站水轮机组分布式健康函数,完成水轮机组机械振动故障判别方法设计,检测水轮机组是否为正常状态,实现机械振动故障判别。实验表明,所提模型可以准确判别故障振动,确保后续及时维修,提高工作效率。
Abstract:
In order to improve the accuracy of mechanical vibration fault diagnosis for hydraulic turbine units in large pumped storage power plants so as to timely repair them , ensure the safe operation of hydraulic turbine equipment in pumped storage power plants , and extend the service life of machinery , a method for mechanical vibration fault diagnosis of hydraulic turbine units is proposed.By using dimensionless processing for the mechanical signals of the hydraulic turbine unit , redundant signals are removed. Then , the weighted distribution of vibration parameters is determined , and the weight of fault characteristic quantity is set.Next , a distributed health function for the hydraulic turbine unit of pumped storage power station is constructed.With the above steps , the design of the mechanical vibration fault discrimination method for the hydraulic turbine unit is completed , and the normal status of the hydraulic turbine unit is detected , so as to achiev mechanical vibration fault diagnosis.Through experiments , it is proved that the proposed model can accurately identify fault vibrations , ensure timely follow up maintenance , and improve work efficiency.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2023-05-06
基金项目:南方电网基金项目( 02910020220301030200016 )
作者简介:蔡喜昌 ( 1981- ),男,广东茂名人,学士,工程师,研究方向为抽水蓄能电站运行维护;冯文嵛 ( 1990- ),男,广西崇左人,学士,工程师,研究方向为抽水蓄能电站运行维护;林杰胜 ( 1995- ),男,广东惠来人,学士,助理工程师,研究方向为抽水蓄能电站运行维护;林泳骏 ( 1998- ),男,广东高州人,学士,助理工程师,研究方向为抽水蓄能电站运行维护;李东璐 ( 1992- ),男,河南南阳人,学士,助理工程师,研究方向为抽水蓄能电站运行维护。
更新日期/Last Update: 2024-08-30