Evidence map›Paper›PMID 39517905›Full record

ArticleSensors (Basel, Switzerland)2024

Recognition of Impact Load on Connecting-Shaft Rotor System Based on Motor Current Signal Analysis.

Kun Zhang, Zhaojian Yang, Qingbao Bao, Jianwen Zhang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

4 authors.

Kun ZhangCollege of Mechanical Engineering, Taiyuan University of Technology, Taiyuan 030024, China.ORCID 0000-0002-3543-0137
Zhaojian YangCollege of Mechanical Engineering, Taiyuan University of Technology, Taiyuan 030024, China.
Qingbao BaoPostdoctoral Science Research Workstation, Taiyuan Heavy Machinery Group Co., Ltd., Taiyuan 030024, China.
Jianwen ZhangCollege of Mathematics, Taiyuan University of Technology, Taiyuan 030024, China.

Funding

Basic Research Program of Shanxi Province (Natural Exploration) 202103021223101National Natural Science Foundation of China 51475318
6 · The paper itself

Abstract

Impact loads affect the operational performance and safety life of rolling equipment's connecting-shaft rotor system, even causing faults and accidents. Therefore, recognizing and investigating impact loads is of great significance. Hence, a load recognition method based on motor current information is proposed in this paper to recognize impact loads on the connecting-shaft rotor system. First, the fast Fourier transform is used to obtain the frequency domain information for the motor's current response signal from the rotor system load recognition test. Consequently, the required load response information can be presented more clearly using the singular value decomposition method to remove the power frequency components in the current signal. Then, wavelet packet decomposition is performed on the signal to generate energy analysis feature vectors. A qualitative recognition of the impact load on the system is achieved by learning vector quantization neural networks; the resulting load recognition results are good. These findings indicate that using the motor current as the analysis signal can solve the problem of the difficult layout for traditional vibration sensors in rolling sites. The preprocessing and recognition method of the current response signal can recognize the impact load, confirming the applicability and feasibility of the proposed method.

Indexed as

feature extractionload recognitionmotor currentrotor system

Identifiers

PMID39517905
PMCPMC11548439

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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.