基于Hilbert−Huang变换的往复式氢气压缩机状态监测系统

Haiyang Li, Diankui Gao, Bin Zhao
{"title":"基于Hilbert−Huang变换的往复式氢气压缩机状态监测系统","authors":"Haiyang Li,&nbsp;Diankui Gao,&nbsp;Bin Zhao","doi":"10.1002/appl.202400204","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>A reciprocating hydrogen compressor status monitoring system for predictive maintenance is developed based on HHT (Hilbert−Huang Transform) with multiple functions, strong applicability, and high accuracy to address the problem of difficulty in identifying fault signals and failure to provide advance warning before faults occur in the reciprocating hydrogen compressor state monitoring system. Design framework of monitoring system is confirmed, and function modules are designed based on LabView platform. HHT is applied to monitor the status of reciprocating hydrogen compressor based on LabView platform. A reciprocating hydrogen compressor is selected as research object, status monitoring analysis is carried out. Five working states of reciprocating hydrogen compressor are collected, which conclude normal state, filler malfunction, cross-head malfunction, air valve malfunction, and piston rod malfunction. HHT is carried out for five signals, and results show that HHT marginal spectrum of five signals has different characteristics. Based on comparison results, precision of HHT ranges from 0.757 to 0.784, recall of HHT ranges from 0.738 to 0.766, F1-score of HHT ranges from to 0.788 to 0.804, HHT has better performance than other two methods. Proposed monitoring system designed in this study provides a comprehensive and efficient online monitoring and data analysis solution for reciprocating hydrogen compressors, which can achieve fault prediction of reciprocating hydrogen compressor, reduce failure rate, and effectively improve the reliability of the compressor oil injection system.</p></div>","PeriodicalId":100109,"journal":{"name":"Applied Research","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/appl.202400204","citationCount":"0","resultStr":"{\"title\":\"Status Monitoring System of Reciprocating Hydrogen Compressor Based on Hilbert−Huang Transform\",\"authors\":\"Haiyang Li,&nbsp;Diankui Gao,&nbsp;Bin Zhao\",\"doi\":\"10.1002/appl.202400204\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>A reciprocating hydrogen compressor status monitoring system for predictive maintenance is developed based on HHT (Hilbert−Huang Transform) with multiple functions, strong applicability, and high accuracy to address the problem of difficulty in identifying fault signals and failure to provide advance warning before faults occur in the reciprocating hydrogen compressor state monitoring system. Design framework of monitoring system is confirmed, and function modules are designed based on LabView platform. HHT is applied to monitor the status of reciprocating hydrogen compressor based on LabView platform. A reciprocating hydrogen compressor is selected as research object, status monitoring analysis is carried out. Five working states of reciprocating hydrogen compressor are collected, which conclude normal state, filler malfunction, cross-head malfunction, air valve malfunction, and piston rod malfunction. HHT is carried out for five signals, and results show that HHT marginal spectrum of five signals has different characteristics. Based on comparison results, precision of HHT ranges from 0.757 to 0.784, recall of HHT ranges from 0.738 to 0.766, F1-score of HHT ranges from to 0.788 to 0.804, HHT has better performance than other two methods. Proposed monitoring system designed in this study provides a comprehensive and efficient online monitoring and data analysis solution for reciprocating hydrogen compressors, which can achieve fault prediction of reciprocating hydrogen compressor, reduce failure rate, and effectively improve the reliability of the compressor oil injection system.</p></div>\",\"PeriodicalId\":100109,\"journal\":{\"name\":\"Applied Research\",\"volume\":\"4 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-10-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/appl.202400204\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/appl.202400204\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Research","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/appl.202400204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

针对往复式氢压缩机状态监测系统存在的故障信号难以识别、故障发生前无法预警的问题,基于HHT (Hilbert−Huang Transform)算法,开发了一种多功能、适用性强、精度高的往复式氢压缩机状态监测系统。确定了监控系统的设计框架,并基于LabView平台进行了功能模块的设计。基于LabView平台,将HHT应用于往复式氢气压缩机的状态监测。以往复式氢气压缩机为研究对象,进行了状态监测分析。收集了往复式氢气压缩机的五种工作状态,分别为正常状态、填料故障、十字头故障、气阀故障和活塞杆故障。对5种信号进行HHT,结果表明5种信号的HHT边际谱具有不同的特征。对比结果表明,HHT的精密度范围为0.757 ~ 0.784,召回率范围为0.738 ~ 0.766,f1评分范围为0.788 ~ 0.804,HHT的性能优于其他两种方法。本研究设计的监测系统为往复式氢气压缩机提供了全面、高效的在线监测和数据分析解决方案,可实现往复式氢气压缩机的故障预测,降低故障率,有效提高压缩机喷油系统的可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Status Monitoring System of Reciprocating Hydrogen Compressor Based on Hilbert−Huang Transform

A reciprocating hydrogen compressor status monitoring system for predictive maintenance is developed based on HHT (Hilbert−Huang Transform) with multiple functions, strong applicability, and high accuracy to address the problem of difficulty in identifying fault signals and failure to provide advance warning before faults occur in the reciprocating hydrogen compressor state monitoring system. Design framework of monitoring system is confirmed, and function modules are designed based on LabView platform. HHT is applied to monitor the status of reciprocating hydrogen compressor based on LabView platform. A reciprocating hydrogen compressor is selected as research object, status monitoring analysis is carried out. Five working states of reciprocating hydrogen compressor are collected, which conclude normal state, filler malfunction, cross-head malfunction, air valve malfunction, and piston rod malfunction. HHT is carried out for five signals, and results show that HHT marginal spectrum of five signals has different characteristics. Based on comparison results, precision of HHT ranges from 0.757 to 0.784, recall of HHT ranges from 0.738 to 0.766, F1-score of HHT ranges from to 0.788 to 0.804, HHT has better performance than other two methods. Proposed monitoring system designed in this study provides a comprehensive and efficient online monitoring and data analysis solution for reciprocating hydrogen compressors, which can achieve fault prediction of reciprocating hydrogen compressor, reduce failure rate, and effectively improve the reliability of the compressor oil injection system.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
0.70
自引率
0.00%
发文量
0
期刊最新文献
A Novel Impedance Platform Based on Printed Polymer Electrodes for Automated Virus Neutralization Assays Influence of Bi2O3 Concentration on Optical and Gamma Ray Shielding Properties of BaTiO3 Ceramics Open-Source Tools for Assessing Cytoskeleton Properties in Pathological Conditions From Microscopy Images: An Application Note Application of Finite Pointset Method to Study Two-Way Coupled Transient Bio-Thermoelastic Effects in Skin Tissue Toward the Automation of the 3D Robotic Coreless Filament Winding Process for High-Performance Composite Materials With Multiple Reinforcement Levels
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1