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首页> 外文会议>Conference on Health Monitoring and Smart Nondestructive Evaluation of Structural and Biological Systems >Real-time health monitoring of a thin composite beam using a passive structural neural system
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Real-time health monitoring of a thin composite beam using a passive structural neural system

机译：一种使用无源结构神经系统的薄复合梁的实时健康监测

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摘要

A small size prototype of a Structural Neural System (SNS) was tested in real time for damage detection in a laboratory setting and the results are presented in this paper. The SNS is a passive online structural health monitoring (SHM) system that can detect small propagating damages in real time before the overall failure of the structure is realized. The passive SHM method is based on the concept of detecting acoustic emissions (AE) due to damage propagating. Propagating cracks were identified near the vicinity of a sensor in a composite specimen during fatigue testing. In the composite specimen, in additions to a propagating crack, fretting occurred because of slipping contact between the load points and the composite specimen. The SNS was able to predict the location of damage due to crack propagation and also detect signals from fretting simultaneously in real time.
机译：实时测试了结构神经系统（SNS）的小尺寸原型进行损坏检测，并在本文中提出了结果。 SNS是一种被动在线结构健康监测（SHM）系统，可以在实现结构的整体故障之前实时检测小传播损坏。被动SHM方法基于由于损坏传播而检测声学发射（AE）的概念。在疲劳检测期间鉴定在复合样品中的传感器附近鉴定传播裂缝。在复合试样中，除了传播裂缝，由于负载点和复合样品之间的触点滑动而发生微动。 SNS能够预测由于裂纹传播引起的损坏的位置，并且还可以实时检测来自烦恼的信号。

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