SPATIAL FILTERING TECHNIQUE-BASED ENHANCEMENT OF THE RECONSTRUCTION ALGORITHM FOR THE PROBABILISTIC INSPECTION OF DAMAGE (RAPID)

L. Lomazzi, Á. González-Jiménez, F. Cadini, A. Manes, M. Giglio
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Abstract

A common active structural health monitoring (SHM) solution for thin-walled structures consists of processing ultrasonic guided waves signals, which are excited and sensed by means of a network of piezoelectric devices installed on the structure, with the purpose of providing a tomographic reconstruction-based damage probability map of the structure. A promising reconstruction algorithm typically employed within this framework is the Reconstruction Algorithm for the Probabilistic Inspection of Damage (RAPID) algorithm, which has been shown to provide satisfactory results in terms of damage detection and localisation. However, this algorithm comes with some disadvantages and minor issues, such as artefacts creation in case an unevenly distributed sensors layout is installed on the structure, which may significantly worsen the damage diagnosis performance of the monitoring framework. In this paper, an enhancement of the original RAPID algorithm is presented, which exploits spatial filtering techniques to reduce possible artificially created artefacts, thus allowing installing on structures any network of sensors without reducing the diagnostic performances. The improved damage localisation accuracy obtained using the proposed algorithm is proven by means of a case study involving a numerical model of a realistic composite panel with an unevenly distributed network of sensors.
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基于空间滤波技术增强的损伤概率检测重构算法(快速)
一种常用的薄壁结构主动健康监测(SHM)解决方案是利用安装在薄壁结构上的压电装置网络对超声导波信号进行处理,以提供基于层析重建的结构损伤概率图。在该框架中通常采用的一种有前途的重建算法是损伤概率检查(RAPID)算法的重建算法,该算法已被证明在损伤检测和定位方面提供了令人满意的结果。然而,该算法也存在一些缺点和小问题,如在结构上安装分布不均匀的传感器布局会产生伪影,这可能会大大降低监测框架的损伤诊断性能。在本文中,提出了原始RAPID算法的增强,该算法利用空间滤波技术来减少可能的人工产生的伪影,从而允许在结构上安装任何传感器网络而不降低诊断性能。通过一个具有非均匀分布传感器网络的实际复合材料面板的数值模型,验证了该算法对损伤定位精度的提高。
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NONLINEAR BULK WAVE PROPAGATION IN A MATERIAL WITH RANDOMLY DISTRIBUTED SYMMETRIC AND ASYMMETRIC HYSTERETIC NONLINEARITY SPATIAL FILTERING TECHNIQUE-BASED ENHANCEMENT OF THE RECONSTRUCTION ALGORITHM FOR THE PROBABILISTIC INSPECTION OF DAMAGE (RAPID) KOOPMAN OPERATOR BASED FAULT DIAGNOSTIC METHODS FOR MECHANICAL SYSTEMS ON THE APPLICATION OF VARIATIONAL AUTO ENCODERS (VAE) FOR DAMAGE DETECTION IN ROLLING ELEMENT BEARINGS INTELLIGENT IDENTIFICATION OF RIVET CORROSION ON STEEL TRUSS BRIDGE BY SINGLE-STAGE DETECTION NETWORK
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