Evidence map›Paper›PMID 41096275›Full record

ArticlePolymers2025

Drilling Surface Quality Analysis of Carbon Fiber-Reinforced Polymers Based on Acoustic Emission Characteristics.

Mengke Yan, Yushu Lai, Yiwei Zhang, Lin Yang, Yan Zheng, Tianlong Wen, Cunxi Pan

Abstract read
In one paragraph

Article in Polymers, 2025. 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
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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

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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

7 authors.

Mengke YanChongqing Engineering Research Center for Advanced Intelligent Manufacturing Technology, Chongqing Three Gorges University, Chongqing 404000, China.
Yushu LaiChongqing Engineering Research Center for Advanced Intelligent Manufacturing Technology, Chongqing Three Gorges University, Chongqing 404000, China.
Yiwei ZhangChongqing Engineering Technology Research Center for Light Alloy and Processing, Chongqing Three Gorges University, Chongqing 404000, China.
Lin YangChongqing Engineering Technology Research Center for Light Alloy and Processing, Chongqing Three Gorges University, Chongqing 404000, China.
Yan ZhengChongqing Engineering Technology Research Center for Light Alloy and Processing, Chongqing Three Gorges University, Chongqing 404000, China.
Tianlong WenChongqing Engineering Research Center for Advanced Intelligent Manufacturing Technology, Chongqing Three Gorges University, Chongqing 404000, China.
Cunxi PanChongqing Engineering Research Center for Advanced Intelligent Manufacturing Technology, Chongqing Three Gorges University, Chongqing 404000, China.

Funding

the General Project of Natural Science Foundation of Chongqing CSTB2025NSCQ-GPX1326the Research Institute of Intelligent Manufacturing Industry Technology of SiChuan Arts and Science university ZNZZ2403; ZNZZ2306the Scientific and technological research project of Chongqing Municipal Education Commission KJQN202401204;KJQN202501215
6 · The paper itself

Abstract

CFRP is extensively utilized in the manufacturing of aerospace equipment owing to its distinctive properties, and hole-making processing continues to be the predominant processing method for this material. However, due to the anisotropy of CFRP, in its processing process, processing damage appears easily, such as stratification, fiber tearing, burrs, etc. These damages will seriously affect the performance of CFRP components in the service process. This work employs acoustic emission (AE) and infrared thermography (IT) techniques to analyze the characteristics of AE signals and temperature signals generated during the CFRP drilling process. Fast Fourier transform (FFT) and short-time Fourier transform (STFT) are used to process the collected AE signals. And in combination with the actual damage morphology, the material removal behavior during the drilling process and the AE signal characteristics corresponding to processing defects are studied. The results show that the time-frequency graph and root mean square (RMS) curve of the AE signal can accurately distinguish the different stages of the drilling process. Through the analysis of the frequency domain characteristics of the AE signal, the specific frequency range of the damage mode of the CFRP composite material during drilling is determined. This paper aims to demonstrate the feasibility of real-time monitoring of the drilling process. By analyzing the relationship between the RMS values of acoustic emission signals and hole surface topography under different drilling parameters, it provides a new approach for the research on online monitoring of CFRP drilling damage and improvement of CFRP machining quality.

Indexed as

acoustic emissioncarbon fiber-reinforced polymer (CFRP)damage identificationdrillingsignal processing

Identifiers

PMID41096275
PMCPMC12526748

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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.