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从超声声发射中提取特征:一种评估挪威云杉树干木材水力脆弱性的工具?

Extraction of features from ultrasound acoustic emissions: a tool to assess the hydraulic vulnerability of Norway spruce trunkwood?

作者信息

Rosner Sabine, Klein Andrea, Wimmer Rupert, Karlsson Bo

机构信息

Institute of Botany, Department of Integrative Biology, BOKU Vienna, Gregor Mendel Str. 33, A-1180 Vienna, Austria.

出版信息

New Phytol. 2006;171(1):105-16. doi: 10.1111/j.1469-8137.2006.01736.x.

DOI:10.1111/j.1469-8137.2006.01736.x
PMID:16771986
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3196831/
Abstract

The aim of this study was to assess the hydraulic vulnerability of Norway spruce (Picea abies) trunkwood by extraction of selected features of acoustic emissions (AEs) detected during dehydration of standard size samples. The hydraulic method was used as the reference method to assess the hydraulic vulnerability of trunkwood of different cambial ages. Vulnerability curves were constructed by plotting the percentage loss of conductivity vs an overpressure of compressed air. Differences in hydraulic vulnerability were very pronounced between juvenile and mature wood samples; therefore, useful AE features, such as peak amplitude, duration and relative energy, could be filtered out. The AE rates of signals clustered by amplitude and duration ranges and the AE energies differed greatly between juvenile and mature wood at identical relative water losses. Vulnerability curves could be constructed by relating the cumulated amount of relative AE energy to the relative loss of water and to xylem tension. AE testing in combination with feature extraction offers a readily automated and easy to use alternative to the hydraulic method.

摘要

本研究的目的是通过提取标准尺寸样本脱水过程中检测到的声发射(AE)的选定特征,评估挪威云杉(Picea abies)树干木材的水力脆弱性。采用水力方法作为参考方法,评估不同形成层年龄树干木材的水力脆弱性。通过绘制电导率损失百分比与压缩空气超压的关系曲线来构建脆弱性曲线。幼龄木材样本和成熟木材样本之间的水力脆弱性差异非常明显;因此,可以筛选出有用的AE特征,如峰值幅度、持续时间和相对能量。在相同的相对水分损失情况下,按幅度和持续时间范围聚类的信号的AE速率以及AE能量在幼龄木材和成熟木材之间差异很大。通过将累积的相对AE能量与相对水分损失和木质部张力相关联,可以构建脆弱性曲线。AE测试与特征提取相结合,为水力方法提供了一种易于自动化且易于使用的替代方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abd7/3196831/02de6e036e53/ukmss-33474-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abd7/3196831/2c876d72b199/ukmss-33474-f0001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abd7/3196831/6ba800f09290/ukmss-33474-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abd7/3196831/22e59d7ac773/ukmss-33474-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abd7/3196831/7bac044b3339/ukmss-33474-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abd7/3196831/02de6e036e53/ukmss-33474-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abd7/3196831/2c876d72b199/ukmss-33474-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abd7/3196831/07b3c7485aab/ukmss-33474-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abd7/3196831/6ba800f09290/ukmss-33474-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abd7/3196831/22e59d7ac773/ukmss-33474-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abd7/3196831/7bac044b3339/ukmss-33474-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abd7/3196831/02de6e036e53/ukmss-33474-f0006.jpg

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