低信号与噪声比的声学发射信号到达时间识别方法基于分数维度比和AR-AIC组合算法
Weigang Zhao1, Shunli Jiang2, Haoran Li1
1School of Safety Engineering and Emergency Management, Shijiazhuang Tiedao University, Shijiazhuang 050043, China.
Ultrasonics
|June 29, 2025
概括
本研究提出了一种用于识别声波发射 (AE) 信号到达时间的新方法,在噪音条件下提高了准确性. 这种方法提高了对混凝土结构的来源定位,减少了高达47%的错误.
科学领域:
- 工程 工程师 工程师 工程师
- 材料科学 材料科学 材料科学
- 信号处理 信号处理
背景情况:
- 准确的声辐射 (AE) 信号到达时间识别对于结构健康监测至关重要.
- 低信号噪声比 (SNR) 的环境对传统的AE分析方法构成重大挑战.
- 像threshold,STA/LTA和AR-AIC这样的现有算法与模糊的到达和低振幅信号作斗争.
研究的目的:
- 开发和评估一种新的方法,用于在低SNR环境中增强AE信号到达时间识别.
- 使用AE信号,提高在混凝土结构中源定位的准确性.
- 为了减轻SNR和信号幅度对AE到达时间检测的影响.
主要方法:
- 集成的碎形尺寸比,以估计潜在的到达时间范围.
- 应用自行回归-Akaike信息标准 (AR-AIC) 算法来精确确定到达时间.
- 在各种SNR条件下的混凝土样本上使用笔断 (PLB) 试验进行实验验证.
主要成果:
- 拟议的碎形尺寸比率和AR-AIC集成方法有效地识别了在具有挑战性的低SNR条件下AE信号到达时间.
- 该方法证明了对SNR和信号幅度变化的稳定性.
- 与传统方法相比,定位错误显著减少,超过值,STA/LTA和AR-AIC的改善分别为47%,23%和17%.
结论:
- 结合的分形维度比和AR-AIC方法为AE信号到达时间识别提供了卓越的性能.
- 这种方法可以在复杂和杂的环境中提高源定位的准确性.
- 这些发现支持采用这种技术来使用AE进行更可靠的结构健康监测.
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