基于声发射技术的混凝土试件弯曲损伤研究

发布时间：2019-05-28 07:13

【摘要】：混凝土桥占桥梁总数的90%,绝大多数既有混凝土桥梁存在一定的损伤。既有混凝土桥的损伤是影响桥梁使用性能的重要因素。声发射技术是检测混凝土损伤的有效方法,声发射检测信号与混凝土内部损伤对应关系研究还不深入,本论文针对声发射信号与混凝土损伤进行研究,具体工作如下:(1)对混凝土试件进行三分点加载弯曲试验,监测加载全过程混凝土应变和声发射特征参数,分析试件不同受力阶段声发射特征参数与损伤关系。混凝土试件加载初期,水泥砂浆和集料的界面存在的微裂缝等原始缺陷,就会产生低幅值、低能量的撞击信号,随着荷载的继续加大,试件内部不断产生新的裂缝,声发射信号活动增强,高幅值信号出现次数增多,同时伴随着能量的多次突发释放。(2)基于小波理论,分析研究了适用于混凝土试件的小波去噪参数选择,当选用db4小波、进行2层小波分解,在Heursure阈值准则下选用软阈值函数进行数据去噪处理是效果最理想的。通过比对去噪前后信号波形图,可以看出运用小波降噪,处理信号保留了原始信号的大部分主要特征,同时去除了一些噪声信号,使采集到的信号更能表征声发射源信号的特征。(3)在对采集到的信号进行小波降噪的基础上,运用互相关分析法,计算出两两传感器接收到声发射信号的时间延迟,进而结合所测时间波速就可以定位出声发射源位置,提高了声发射损伤定位的精确性。
[Abstract]:Concrete bridges account for 90% of the total number of bridges, and most of the existing concrete bridges have certain damage. The damage of existing concrete bridge is an important factor affecting the performance of bridge. Acoustic emission technology is an effective method to detect concrete damage. The corresponding relationship between acoustic emission detection signal and concrete internal damage is not deeply studied. In this paper, the acoustic emission signal and concrete damage are studied. The specific work is as follows: (1) the three-point loading bending test of concrete specimens is carried out, the strain and acoustic emission characteristic parameters of concrete are monitored, and the relationship between acoustic emission characteristic parameters and damage in different stress stages is analyzed. At the beginning of loading, the original defects such as micro cracks in the interface between cement mortar and aggregate will produce low amplitude and low energy impact signals. with the continuous increase of load, new cracks will continue to occur in the specimen. The activity of acoustic emission signal is enhanced, the frequency of high amplitude signal is increased, and the sudden release of energy is accompanied by multiple bursts of energy. (2) based on wavelet theory, the selection of wavelet denoising parameters suitable for concrete specimens is analyzed and studied, and db4 wavelet is selected. The two-layer wavelet decomposition is carried out, and the soft threshold function is selected for data denoising under the Heursure threshold criterion. By comparing the signal waveform before and after denoising, we can see that by using wavelet denoising, the processed signal preserves most of the main characteristics of the original signal, and at the same time removes some noise signals. The collected signal can better represent the characteristics of the acoustic emission source signal. (3) on the basis of wavelet denoising of the collected signal, the time delay of receiving the acoustic emission signal by the pairwise sensor is calculated by using the cross-correlation analysis method. Combined with the measured time wave velocity, the position of acoustic emission source can be located, and the accuracy of acoustic emission damage location can be improved.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U441.4

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