算法
结构健康监测
计算机科学
职位(财务)
信号(编程语言)
子空间拓扑
补偿(心理学)
信号子空间
相(物质)
噪音(视频)
传感器阵列
人工智能
工程类
机器学习
心理学
化学
结构工程
财务
有机化学
精神分析
经济
图像(数学)
程序设计语言
作者
Fei Zheng,Shenfang Yuan,Yuan Liu,Qiuhui Xu
标识
DOI:10.1177/10775463231167234
摘要
The increasing use of composite materials on aircraft structures, most of which are plate-like, has attracted much attention for damage monitoring based on guided wave as a kind of structural health monitoring (SHM) method. The multiple signal classification (MUSIC) algorithm is a directional scanning and searching method to unbiasedly estimate the signal features in terms of the orthogonal attributes between signal subspace and noise subspace. The MUSIC algorithm is gradually shifted into the field of SHM used for damage localization. However, the anisotropy of the composites and the sensor position errors cause the phase errors of the array response signal, resulting in a decrease in the accuracy of the MUSIC method. In addition, the complexity of the array monitoring network causes a significant increase in the amount of operations for signal information processing, making online real-time monitoring challenging. In order to reduce the impact of multiple forms of array errors on the MUSIC algorithm and to improve the efficiency of it, this paper proposes an efficient damage imaging method for composite structure based on self-correcting phase error compensation MUSIC algorithm, which compensates for the array phase errors caused by structural anisotropy and sensor position errors, and achieves high efficiency. The method has been verified on a stiffened composite structure, and the results show its superiority and effectiveness.
科研通智能强力驱动
Strongly Powered by AbleSci AI