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Structural health assessment of prefabricated concrete elements using Acoustic Emission: Towards an optimized damage sensing tool

机译:采用声发射预制混凝土元件的结构健康评估:朝向优化的损伤感应工具

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The design feasibility and structural integrity of prefabricated construction elements is assessed (concrete cantilever slab carrying thermal insulation break reinforced with steel/basalt rebars and ultra-high-performance concrete) by performing incremental bending tests. The developed damage mechanisms govern failure, therefore their identification appears crucial: concrete cracking, rebars-concrete interface debonding, rebars slippage, concrete crush under compression. However, the complex fracture cannot be effectively characterized by measuring the deterioration of the mechanical properties. In this study, Acoustic Emission (AE) is applied to highlight internal damage progress. It is found based on cumulative AE hits distribution under incremental load and considering the Kaiser and Felicity effects, damage initiation is identified. The damage severity is quantified using Load/Calm ratios. AE sources localization identifies the moment at which the rebars plastically deform; debond from concrete; slip and when concrete cracks and crushes under compression. The damage mechanisms are discriminated based on acoustic signal features distribution as damage evolves (specifically, average frequency and the ratio of rise time over amplitude). It is shown that AE appears an essential and accurate monitoring method that fully characterizes the damage on complex structures. The promising results open new horizons towards the design of fully autonomous prefabricated elements carrying a smart on-line AE sensing tool. (C) 2019 Elsevier Ltd. All rights reserved.
机译:通过进行增量弯曲试验评估预制结构元件的设计可行性和结构完整性(混凝土悬臂板携带绝热断裂和超高性能混凝土)。发达的损坏机制控制失败,因此它们的识别显得至关重要:混凝土裂缝,钢筋混凝土界面剥离,钢筋滑动,压缩下的混凝土粉碎。然而,通过测量机械性能的劣化,不能有效地表征复杂的骨折。在本研究中,应用声学发射(AE)以突出内部损伤进展。基于累积AE在增量负荷下的累积AE分布并考虑到kaiser和富集效应,确定了损伤启动。使用负载/平静比率量化损伤严重程度。 AE Sources定位识别钢筋塑性变形的那一刻;从混凝土中的借方;滑动和在压缩下混凝土裂缝和压碎时。基于声信号特征分布的损坏机制被区分,因为损坏演变(具体地,平均频率和上升时间的比率)。结果表明,AE似乎是一种必要和准确的监测方法,可以完全表征复杂结构的损坏。有希望的结果开辟了新的视野,朝着携带智能在线AE传感工具的完全自主预制元件设计。 (c)2019 Elsevier Ltd.保留所有权利。

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