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Experimental research on crack damage detection of concrete beam based on PZT wave method

机译:基于PZT波法的混凝土梁裂缝损伤检测的试验研究

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Concrete cracks which are gradually extended, damaged and destructed by the load have become difficult to be solved in engineering. Due to the advantages of convenient production, high sensitivity, reasonable performance-price ratio, self-sensing, piezoelectric ceramic (such as PZT) smart aggregates used as sensor and actuator are embedded in the reinforced concrete beams to generate sin-sweep excitation signals on-line and detect real-time signals with digital oscilloscope before and after damage. The optimal extraction damage signals are extracted and statistical pattern recognition algorithm of wavelet decomposition about the detection signals is established by wavelet analysis and statistical characteristics analysis. The statistical distribution of signal amplitude and the relevant damage indicators are proposed for the use of active health monitoring and energy damage principles. The results of loading tests show that the amplitude of active monitoring signal produced a larger attenuation after damage and sweep wave signals used in active health monitoring are effective in identifying the different health status of structure. The statistical pattern recognition algorithm based on wavelet packet decomposition can effectively detect crack damages of concrete structure. This technology may open a new road for active and permanent monitoring and damage detection on line as well as development of active health monitoring system based on probability statistics of piezoelectric concrete.
机译:在荷载作用下逐渐扩展,损坏和破坏的混凝土裂缝已变得难以解决。由于生产方便,灵敏度高,性能价格比合理,将自感应压电压电陶瓷(如PZT)智能骨料用作传感器和执行器,因此可以将其嵌入钢筋混凝土梁中,从而在正弦波上产生正弦扫描激励信号。在损坏之前和之后使用数字示波器对数据进行在线测量并检测实时信号。通过小波分析和统计特征分析,提取了最优的提取损伤信号,建立了检测信号的小波分解统计模式识别算法。建议使用主动健康监测和能量损伤原理来统计信号幅度和相关损伤指标的统计分布。载荷测试结果表明,主动监测信号的振幅在损伤后产生较大的衰减,主动健康监测中使用的扫描波信号可以有效地识别结构的不同健康状态。基于小波包分解的统计模式识别算法可以有效地检测混凝土结构的裂纹损伤。该技术可为主动和永久性在线监测以及在线损伤检测以及基于压电混凝土概率统计的主动健康监测系统的开发开辟一条新道路。

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