Status Monitoring System of Reciprocating Hydrogen Compressor Based on Hilbert−Huang Transform

ABSTRACT 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.

Authors

Institutions

Publication Details

Journal
Applied Research
Published
2024-10-06
DOI
https://doi.org/10.1002/appl.202400204
Citations
1
Primary Topic
Advanced Sensor and Control Systems
Type
article
Field-Weighted Citation Impact
0.33
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Status Monitoring System of Reciprocating Hydrogen Compressor Based on Hilbert−Huang Transform

Haiyang Li, Diankui Gao, Bin Zhao
1 citations
Applied Research
Advanced Sensor and Control Systems
0.33
article

Status Monitoring System of Reciprocating Hydrogen Compressor Based on Hilbert−Huang Transform

Haiyang Li, Diankui Gao, Bin Zhao
article en
1 citations

Abstract

ABSTRACT 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.

Applied ResearchVol. 4(1)
Liaoning Shihua University (CN)
Affordable and clean energy
Openalex Percentile: Top 41%
Advanced Sensor and Control Systems
0.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.