概率逻辑
复合数
融合
计算机科学
材料科学
人工智能
算法
哲学
语言学
作者
Deshuang Deng,Xu Zeng,Zhengyan Yang,Yang Yu,Sheng Zhang,Shuyi Ma,Hao Xu,Lei Yang,Zhanjun Wu
标识
DOI:10.1177/14759217241233181
摘要
Since the internal barely visible damage of aircraft composite structures caused by the impact is a critical problem, impact monitoring is essential for the integrity and reliability of aircraft composite structures. This paper presents a multi-frequency probabilistic imaging fusion method for localizing impacts on aircraft composite structures. To capture the impact signals, a network of distributed sensors is mounted on the structure. The impact signals are then processed using the continuous wavelet transform (CWT) to extract the multi-frequency narrowband Lamb wave signals. The time difference of arrival (TDOA), a key feature of the impact source, is measured using averaging techniques employed in the normalized variance sequence. Subsequently, a probabilistic imaging function is established, and the TDOA of narrowband Lamb wave signals at each frequency is used as the feature input to generate the multi-frequency probabilistic imaging results. To determine the performance of the imaging results at each frequency, an efficiency index is introduced, allowing for the retention or abandonment of the imaging results. By utilizing the retained multi-frequency probabilistic imaging results, the proposed method achieves impact localization through imaging fusion. Experimental verification is conducted on a stiffened aircraft composite panel, and a comparison is made with two existing methods: the hyperbolic locus imaging method and the virtual time reversal imaging method. The results show that the proposed method can significantly improve localization accuracy compared to the existing methods, and is effective even in the presence of measurement noise.
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