Evidence map›Paper›PMID 39224351›Full record

ArticleHeliyon2024

ResNet diagnosis of rotor faults in oil transfer pumps.

Lei Chen, Liang Dong, Zhi-Cai Wu, Chuan-Han Fan, Wei-Hua Shi, Hong-Gang Li, Ru-Nan Hua, Cui Dai

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Lei ChenResearch Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang, Jiangsu, 212013, China.
Liang DongResearch Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang, Jiangsu, 212013, China.
Zhi-Cai WuResearch Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang, Jiangsu, 212013, China.
Chuan-Han FanResearch Center of Fluid Machinery Engineering and Technology, Jiangsu University, Zhenjiang, Jiangsu, 212013, China.
Wei-Hua ShiWuhan Second Ship Design & Research Institute, Wuhan, 430060, China.
Hong-Gang LiWuhan Second Ship Design & Research Institute, Wuhan, 430060, China.
Ru-Nan HuaWuhan Second Ship Design & Research Institute, Wuhan, 430060, China.
Cui DaiSchool of Energy and Power Engineering, Jiangsu University, Zhenjiang, Jiangsu, 212013, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To address rotor imbalance and misalignment in oil transfer pumps, an innovative diagnostic framework using Residual Network (ResNet) is proposed. The model incorporates advanced signal processing algorithms and strategic sensor placement to enhance diagnostic efficacy. A fault simulation test rig captured vibration signals from eight key measurement points on the pump. One-dimensional and multi-dimensional signal processing techniques generated comprehensive datasets for training and validating the model. Sensor placement optimization, focusing on the bearing seat's axial direction, inlet flange's vertical direction, and outlet flange's axial direction, increased rotor fault sensitivity. Time-frequency data processed via Short-Time Fourier Transform (STFT) achieved the highest diagnostic accuracy, surpassing 98 %. This study highlights the importance of optimal signal processing and precise sensor placement in improving the accuracy of diagnosing rotor faults in oil transfer pumps, thus enhancing the operational reliability and efficiency of energy transportation systems.

Indexed as

Oil transfer pumpResidual networks (ResNet)Rotor fault diagnosisTime-frequency analysisVibration analysis

Identifiers

PMID39224351
PMCPMC11367493

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.