分布式光纤声学传感(DAS)技术在地下工程安全监测中发挥着越来越重要的作用,其中入侵事件辨识和震源定位是关键。针对单一方法P波初至数据震源稳定性较差、震源定位未考虑P波初至数据不确定度的问题,提出一种基于P波初至数据自适应筛选和考虑其不确定度的分布式光纤入侵事件震源贝叶斯定位方法。具体地,首先建立随距离衰减的入侵事件震源定位目标函数,研发多种P波初至数据自适应筛选和震源初定位方法,进而提出考虑P波初至数据不确定度的震源贝叶斯定位方法,给出震源定位结果及其不确定度。某地下排水洞入侵事件震源定位测试表明:(1) 与入侵事件位置较近的传感器数据具有明显更大的定位权重,而传播距离较远传感器数据的定位权重趋于零;(2) 对于传播距离较近的传感器,自适应优选后的P波初至时间与理论传播时间具有良好的一致性;(3) 考虑P波初至不确定度的震源贝叶斯定位能够快速收敛,震源定位结果在水平方向的不确定度呈圆形分布,而在垂直方向的不确定度呈椭圆分布,测试事件定位误差在1 m以内;(4) 岩石掉落、渗透水释放、人员行走、人工敲击试验的平均定位误差分别为0.98 m、0.81 m、1.82 m和0.35 m。本文方法为P波初至数据自适应筛选和震源定位结果不确定度分析提供了一种新途径。
Distributed acoustic sensing (DAS) technology plays an increasingly important role in underground engineering safety monitoring where the identification of intrusion events and source localization are key issues. In response to the issues of poor location stability of single method-based P-wave arrival time data and inconsideration of P-wave arrival time data uncertainty in source localization, this study proposed an intrusion event Bayesian source localization method for distributed acoustic sensing that adapted the selection of P-wave arrival time data and considered its uncertainty. Specifically, we established a source localization objective function for intrusion events that attenuates with distance, developed a P-wave arrival time data adaptive selection and source preliminary localization method, and then proposed a Bayesian source localization method that considered the uncertainty of P-wave arrival time data, providing the source localization results and its uncertainty. Tests on intrusion event source localization in the drainage tunnel show that: (1) Sensor data closer to the intrusion event location have significantly greater localization weight, while the weights of sensor data from further distances tend to zero; (2) For sensors closer to the propagation distance, the adaptively selected P-wave arrival time is consistent with the theoretical propagation time; (3) The Bayesian source localization considering P-wave arrival time uncertainty converges quickly, with the source localization results showing a circular distribution of uncertainty in the horizontal direction and an elliptical distribution in the vertical direction, with an intrusion event localization error within 1 meter; (4) The average location errors of rock fall, water release, human walking, and manual knocking tests are 0.98 m, 0.81 m, 1.82 m and 0.35 m, respectively. In summary, this study provides a new approach to the adaptive selection of P-wave arrival time data and the analysis of uncertainty in source localization results.
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