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Application of Blind Source Separation in Ultrasonic NDE

机译:盲源分离在超声无损检测中的应用

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摘要

Blind source separation (BSS) allows the recovery of unknown signals from observed signals mixed by an unknown propagation medium, and is a promising technique for signal processing and data analysis. In ultrasonic nondestructive evaluation (NDE), BSS can serve at least three purposes: defect classification, system modeling and noise reduction. This paper discusses the application of BSS in ultrasonic NDE, and explores the implementation of independent component analysis (ICA) in separation of ultrasonic signals. Simulation results were given, which showed that different source signals can be separated using ICA, and the conclusion is that BSS can play a very important role in ultrasonic NDE.
机译:盲源分离(BSS)可以从未知传播介质混合的观察信号中恢复未知信号,这是一种有前途的信号处理和数据分析技术。在超声无损评估(NDE)中,BSS至少可以达到三个目的:缺陷分类,系统建模和降噪。本文讨论了BSS在超声NDE中的应用,并探讨了独立分量分析(ICA)在超声信号分离中的实现。仿真结果表明,使用ICA可以分离不同的信号源,结论是BSS在超声NDE中起着非常重要的作用。

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