Xia Yang, Minghui Zhang, Hongbing Chen, Hong Hao, Qingzhao Kong
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引用次数: 0
Abstract
Concrete is the most commonly used construction material in infrastructural projects, but it may suffer from damages because of the heavy loads, fatigue, and harsh service environments. Therefore, it is crucial to detect damage for evaluating the structural conditions and providing guidance for daily maintenance and timely alarm. This paper presents a novel method for damage assessment that offers an easy-carried detection process with a large monitoring range. The proposed method involves exciting stress waves using a force-hammer and receiving them with piezoceramics pasted on the structure. The structural conditions are then evaluated using the Pearson correlation coefficient (PCC) of stress waves received from different stages. To verify the feasibility of the proposed method, a numerical model is innovatively established to study the stress wave propagation in a reinforced concrete (RC) beam with actual damage induced by the external load based on the concrete damaged plasticity (CDP) model. The experimental study is then conducted to demonstrate the effectiveness of the method and the accuracy of the numerical simulation. The numerical and experimental results show a good correlation, illustrating that the proposed method can not only effectively distinguish whether damage occurs but also determine the structural condition from the elastic phase to failure. The proposed monitoring method in this study has great potential for fast damage assessment of RC structures for both lab research and practical applications.
期刊介绍:
The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications.
Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics.
Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.