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基于声发射信号的渐进破坏过程中木材的临界状态分析。

Analysis of critical states based on acoustic emission signals during progressive failure of wood.

机构信息

Department of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming, Yunnan, China.

出版信息

PLoS One. 2024 May 16;19(5):e0302528. doi: 10.1371/journal.pone.0302528. eCollection 2024.

Abstract

The analysis of critical states during fracture of wood materials is crucial for wood building safety monitoring, wood processing, etc. In this paper, beech and camphor pine are selected as the research objects, and the acoustic emission signals during the fracture process of the specimens are analyzed by three-point bending load experiments. On the one hand, the critical state interval of a complex acoustic emission signal system is determined by selecting characteristic parameters in the natural time domain. On the other hand, an improved method of b_value analysis in the natural time domain is proposed based on the characteristics of the acoustic emission signal. The K-value, which represents the beginning of the critical state of a complex acoustic emission signal system, is further defined by the improved method of b_value in the natural time domain. For beech, the analysis of critical state time based on characteristic parameters can predict the "collapse" time 8.01 s in advance, while for camphor pines, 3.74 s in advance. K-value can be analyzed at least 3 s in advance of the system "crash" time for beech and 4 s in advance of the system "crash" time for camphor pine. The results show that compared with traditional time-domain acoustic emission signal analysis, natural time-domain acoustic emission signal analysis can discover more available feature information to characterize the state of the signal. Both the characteristic parameters and Natural_Time_b_value analysis in the natural time domain can effectively characterize the time when the complex acoustic emission signal system enters the critical state. Critical state analysis can provide new ideas for wood health monitoring and complex signal processing, etc.

摘要

木材材料断裂过程中的临界状态分析对于木质建筑安全监测、木材加工等至关重要。本文选择山毛榉和樟子松作为研究对象,通过三点弯曲载荷实验对试件断裂过程中的声发射信号进行分析。一方面,通过选择自然时域中的特征参数来确定复杂声发射信号系统的临界状态间隔。另一方面,基于声发射信号的特点,提出了一种改进的自然时域 b 值分析方法。通过改进的自然时域 b 值分析方法,定义了代表复杂声发射信号系统临界状态开始的 K 值。对于山毛榉,基于特征参数的临界状态时间分析可以提前 8.01 秒预测“崩溃”时间,而对于樟子松,可以提前 3.74 秒预测。对于山毛榉,K 值可以在系统“崩溃”时间提前至少 3 秒进行分析,而对于樟子松,K 值可以在系统“崩溃”时间提前 4 秒进行分析。结果表明,与传统的时域声发射信号分析相比,自然时域声发射信号分析可以发现更多可用的特征信息来描述信号的状态。自然时域中的特征参数和自然时间 b 值分析都可以有效地描述复杂声发射信号系统进入临界状态的时间。临界状态分析可为木材健康监测和复杂信号处理等提供新的思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4904/11098311/60ab965e9447/pone.0302528.g001.jpg

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