• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

用于检测和识别氧化物基陶瓷基复合材料损伤的不同频率分辨率声发射传感器的数据合并

Data Merging of AE Sensors with Different Frequency Resolution for the Detection and Identification of Damage in Oxide-Based Ceramic Matrix Composites.

作者信息

Guel Nicolas, Hamam Zeina, Godin Nathalie, Reynaud Pascal, Caty Olivier, Bouillon Florent, Paillassa Aude

机构信息

IRT Saint-Exupéry, Esplanade des Arts et Métiers, F-33405 Talence CEDEX, France.

INSA Lyon, MATEIS, University of Lyon, CNRS UMR-5510, 7 avenue Jean Capelle, F-69621 Villeurbanne CEDEX, France.

出版信息

Materials (Basel). 2020 Oct 21;13(20):4691. doi: 10.3390/ma13204691.

DOI:10.3390/ma13204691
PMID:33096827
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7589791/
Abstract

In this paper, acoustic emission data fusion based on multiple measurements is presented for damage detection and identification in oxide-based ceramic matrix composites. Multi-AE (acoustic emission) sensor fusion is considered with the aim of a better identification of damage mechanisms. In this context, tensile tests were conducted on ceramic matrix composites, fabricated with 3M™ Nextel™ 610 fibers and aluminosilicate matrix, with two kinds of AE sensors. Redundant and complementary sensor data were merged to enhance AE system capability and reliability. Data fusion led to consistent signal clustering with an unsupervised procedure. A correlation between these clusters and the damage mechanisms was established thanks to in situ observations. The complementarity of the information from both sensors greatly improves the characterization of sources for their classification. Moreover, this complementarity allows features to be perceived more precisely than using only the information from one kind of sensor.

摘要

本文提出了基于多测量的声发射数据融合方法，用于氧化物基陶瓷基复合材料的损伤检测与识别。考虑采用多声发射（AE）传感器融合，以更好地识别损伤机制。在此背景下，使用两种AE传感器对由3M™ Nextel™ 610纤维和硅铝酸盐基体制造的陶瓷基复合材料进行了拉伸试验。将冗余和互补的传感器数据进行合并，以增强AE系统的能力和可靠性。通过无监督程序，数据融合实现了一致的信号聚类。借助原位观察，建立了这些聚类与损伤机制之间的关联。来自两种传感器的信息互补性极大地改善了源特征以进行分类。此外，这种互补性使得特征比仅使用一种传感器的信息时能被更精确地感知。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/2eafeb44529a/materials-13-04691-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/a1cf7e15ccbe/materials-13-04691-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/054835e13c45/materials-13-04691-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/662f7971a679/materials-13-04691-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/130a661f9c7c/materials-13-04691-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/8ea987eb6edd/materials-13-04691-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/c8ecce214000/materials-13-04691-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/6eb08b8dc174/materials-13-04691-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/f1f5c5dfd4af/materials-13-04691-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/a4e9c2d7ad85/materials-13-04691-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/0bfaa69c74c7/materials-13-04691-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/06c1556f7ea1/materials-13-04691-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/57860545cbd2/materials-13-04691-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/96e51d8f050c/materials-13-04691-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/88fcbb0c8673/materials-13-04691-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/b04a1426a0f5/materials-13-04691-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/035f59817569/materials-13-04691-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/4d8267398a4a/materials-13-04691-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/a670823ba785/materials-13-04691-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/a12bcb60e553/materials-13-04691-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/f7bfc5358cf1/materials-13-04691-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/2eafeb44529a/materials-13-04691-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/a1cf7e15ccbe/materials-13-04691-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/054835e13c45/materials-13-04691-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/662f7971a679/materials-13-04691-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/130a661f9c7c/materials-13-04691-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/8ea987eb6edd/materials-13-04691-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/c8ecce214000/materials-13-04691-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/6eb08b8dc174/materials-13-04691-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/f1f5c5dfd4af/materials-13-04691-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/a4e9c2d7ad85/materials-13-04691-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/0bfaa69c74c7/materials-13-04691-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/06c1556f7ea1/materials-13-04691-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/57860545cbd2/materials-13-04691-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/96e51d8f050c/materials-13-04691-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/88fcbb0c8673/materials-13-04691-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/b04a1426a0f5/materials-13-04691-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/035f59817569/materials-13-04691-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/4d8267398a4a/materials-13-04691-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/a670823ba785/materials-13-04691-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/a12bcb60e553/materials-13-04691-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/f7bfc5358cf1/materials-13-04691-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce5c/7589791/2eafeb44529a/materials-13-04691-g021.jpg

相似文献

1
Data Merging of AE Sensors with Different Frequency Resolution for the Detection and Identification of Damage in Oxide-Based Ceramic Matrix Composites.用于检测和识别氧化物基陶瓷基复合材料损伤的不同频率分辨率声发射传感器的数据合并
Materials (Basel). 2020 Oct 21;13(20):4691. doi: 10.3390/ma13204691.
2
Damage Determination in Ceramic Composites Subject to Tensile Fatigue Using Acoustic Emission.使用声发射技术对承受拉伸疲劳的陶瓷复合材料进行损伤判定
Materials (Basel). 2018 Dec 6;11(12):2477. doi: 10.3390/ma11122477.
3
Acoustic Emission Monitoring of Carbon Fibre Reinforced Composites with Embedded Sensors for In-Situ Damage Identification.基于嵌入式传感器的声发射监测碳纤维复合材料的实时损伤识别。
Sensors (Basel). 2021 Oct 19;21(20):6926. doi: 10.3390/s21206926.
4
A Review on Acoustic Emission Testing for Structural Health Monitoring of Polymer-Based Composites.基于聚合物的复合材料结构健康监测的声发射测试综述
Sensors (Basel). 2023 Aug 4;23(15):6945. doi: 10.3390/s23156945.
5
Damage accumulation in cyclically-loaded glass-ceramic matrix composites monitored by acoustic emission.通过声发射监测循环加载的玻璃陶瓷基复合材料中的损伤累积。
ScientificWorldJournal. 2013 Nov 28;2013:869467. doi: 10.1155/2013/869467. eCollection 2013.
6
Acoustic Emission Signal Characterisation of Failure Mechanisms in CFRP Composites Using Dual-Sensor Approach and Spectral Clustering Technique.基于双传感器方法和谱聚类技术的碳纤维增强复合材料（CFRP）失效机制的声发射信号表征
Polymers (Basel). 2022 Dec 22;15(1):47. doi: 10.3390/polym15010047.
7
Reduction in the Sensor Effect on Acoustic Emission Data to Create a Generalizable Library by Data Merging.通过数据合并减少传感器对声发射数据的影响以创建可通用的库。
Sensors (Basel). 2024 Apr 10;24(8):2421. doi: 10.3390/s24082421.
8
Characterization of piezoelectric wafer active sensor for acoustic emission sensing.压电晶片主动传感器用于声发射传感的特性研究。
Ultrasonics. 2019 Feb;92:35-49. doi: 10.1016/j.ultras.2018.08.020. Epub 2018 Sep 1.
9
A Pattern Recognition Approach to Acoustic Emission Data Originating from Fatigue of Wind Turbine Blades.一种针对源自风力涡轮机叶片疲劳的声发射数据的模式识别方法。
Sensors (Basel). 2017 Nov 1;17(11):2507. doi: 10.3390/s17112507.
10
Nondestructive damage evaluation in ceramic matrix composites for aerospace applications.用于航空航天应用的陶瓷基复合材料的无损损伤评估。
ScientificWorldJournal. 2013 Jul 11;2013:715945. doi: 10.1155/2013/715945. Print 2013.

引用本文的文献

1
Tension and Shear Behaviour of Basalt Fiber Bio-Composites with Digital Image Correlation and Acoustic Emission Monitoring.基于数字图像相关和声发射监测的玄武岩纤维生物复合材料的拉伸与剪切行为
Polymers (Basel). 2024 May 9;16(10):1331. doi: 10.3390/polym16101331.
2
Reduction in the Sensor Effect on Acoustic Emission Data to Create a Generalizable Library by Data Merging.通过数据合并减少传感器对声发射数据的影响以创建可通用的库。
Sensors (Basel). 2024 Apr 10;24(8):2421. doi: 10.3390/s24082421.
3
Experimental and Molecular Dynamics Simulation Study on Sol-Gel Conversion Process of Aluminum Carboxylate System.

本文引用的文献

1
A cluster separation measure.一种聚类分离度量。
IEEE Trans Pattern Anal Mach Intell. 1979 Feb;1(2):224-7.
羧酸铝体系溶胶-凝胶转变过程的实验与分子动力学模拟研究
Materials (Basel). 2022 Apr 6;15(7):2704. doi: 10.3390/ma15072704.
4
Transverse Cracking Induced Acoustic Emission in Carbon Fiber-Epoxy Matrix Composite Laminates.碳纤维-环氧树脂基复合材料层压板中横向开裂引发的声发射
Materials (Basel). 2022 Jan 5;15(1):394. doi: 10.3390/ma15010394.