基于振动感知的混凝土铺面板底脱空识别方法

水泥混凝土铺面在使用过程中常由于冲刷和沉降产生脱空，进而诱发断板、错台等病害，严重影响铺面使用性能。为此，提出一种基于振动感知的混凝土铺面板底脱空识别方法，以有效控制混凝土铺面的结构性损坏。通过有限元数值模拟与室内试验，发现板底脱空会影响铺面板局部振动的频谱分布，且影响程度与脱空面积、位置等因素相关。在此基础上，采用分布式光纤传感技术搭建铺面板振动感知系统，分布式地采集铺面板振动特性；利用时频分析技术解析铺面板振动特性，捕获振动频谱特征；研究不同脱空状况下铺面板局部的振动频谱特征。分析结果表明：脱空状况对20~150 Hz频段上频谱特征的影响显著；以该频段为敏感频段，计算加权频率的变化量，并以此为脱空监测指标，提出基于振动感知的混凝土铺面板底脱空识别方法。于上海龙华机场开展现场试验，在3块铺面板内搭建了分布式振动感知系统；采集了12个测点不同日期的动态弯沉与振动特性数据，比较了振动感知法和传统弯沉法的脱空识别结果。试验结果表明：2种方法的识别结果趋于一致且具有较好的相关性，验证了振动感知法用于脱空识别的可行性。

Identification of Cavities Underneath Concrete Pavement Based on Pavement Vibration

Cavities beneath concrete pavement slabs, usually resulting from erosion or foundation settlement, increase the flexural-tensile stress in the slabs, which may cause distresses, such as joint faults and fracture. To avoid such distresses, this study proposes a vibration-based method for the identification of cavities underneath concrete pavements. Through finite element analysis, it was found that the cavities significantly affected the local vibration characteristics in terms of the frequency spectrum; however, they had negligible effects at other positions. Additionally, the location and extent of the cavities affected the local frequency spectrum. On this basis, a distributed optical vibration sensing-system (DOVS) was developed and utilized to measure the vibration characteristics of the concrete pavement. Furthermore, a laboratory test was conducted to study the influence of the extent of cavities, and the frequency spectrum was obtained using time-frequency analysis. The correlation between the frequency spectrum and the extent of cavities was studied, and it was observed that the spectrum of 20-150 Hz was sensitive to the extent of cavities, and hence, an index expressed as "weighted frequency" was used to identify the cavities. During the field tests, the DOVS was established in three concrete pavement slabs at Longhua Airport, Shanghai. This vibration-based cavity identification method was compared with other conventional deflection-based methods, and a good coherence was observed between the identification results of these two methods, indicating that the vibration-based method is reliable for cavity identification.