Monitoring rock mass damaging through the analysis of seismic records is an affirmed tool to manage rock fall risk in view of mitigation strategies. This study proposes a novel approach, named DAmping RaTio Anomalies Monitoring (DaRtAM), to detect the rock mass damaging by measuring variation over time of the damping ratio related to in-situ recorded vibrational events. Although damping-based damage detection techniques are well known for structural monitoring, only few applications exist for rock mass damage investigation not including in-situ long term rock mass monitoring. Here, a three-month-long seismic dataset recorded on a rock wall (Acuto Field Laboratory) by means of six one-component accelerometers was analysed with a STA/LTA algorithm that allowed to extract 19013 vibrational events. The damping ratio of the signals was derived as a function of frequency, averaged in a daily time window and analysed over time to output short-term anomalies and long-term trend. Although the limited time period analysed did not allow to observe significant trend variation of the damping ratio, 131 short-term anomalies were found in the collected seismic records. As it results from this study, the proposed approach is suitable for detecting rock mass damaging and, as a future perspective, will be applied to yearly-lasting vibrational datasets. This approach may be more effective with data acquired in environments characterised by recurrent forcings, such as coastal cliffs forced by sea and wind storms, rock walls stressed by thermal cycles, quarry walls involved in human activities or rocky trenches close to roads and railways.

通过对地震记录的分析来监测岩体破坏是根据缓解策略来管理落石风险的公认工具。这项研究提出了一种新方法，称为阻尼比异常监测 (DaRtAM)，通过测量与现场记录的振动事件相关的阻尼比随时间的变化来检测岩体损坏。尽管基于阻尼的损伤检测技术在结构监测方面是众所周知的，但只有少数应用于岩体损伤调查，不包括原位长期岩体监测。在这里，使用 STA/LTA ​​算法分析了通过六个单分量加速度计记录在岩壁（Acuto Field Laboratory）上的为期三个月的地震数据集，该算法允许提取 19013 个振动事件。信号的阻尼比作为频率的函数导出，在每日时间窗口中取平均值，并随着时间的推移进行分析以输出短期异常和长期趋势。虽然分析的有限时间段无法观察到阻尼比的显着趋势变化，但在收集的地震记录中发现了131个短期异常。由于这项研究的结果，所提出的方法适用于检测岩体损坏，并且从未来的角度来看，将应用于年持续的振动数据集。对于在具有以下特征的环境中获取的数据，这种方法可能更有效经常性的强迫，例如海浪和风暴迫使海岸悬崖、热循环压力下的岩壁、人类活动所涉及的采石场墙或靠近公路和铁路的岩石沟渠。