【摘要】 针对传统矿区边坡滑坡预警方法未能有效考虑滑坡区域地形特征对滑坡过程影响的问题,提出了一种基于动态时间衰减权重(Dynamic Time Decay Weight, DTDW)的自适应预警阈值滑坡预警方法。首先,在对雷达图像数据进行处理前,采用自动异常值检测与修复算法,以减少数据异常,提升监测数据质量;其次,对经过检测的时序雷达形变图像进行处理,提取最大形变区域作为研究区,并计算该区域内多项监测参数(包括速度、加速度与相干性);随后,引入动态时间衰减权重(DTDW),通过为历史时刻的形变图像参数赋予不同程度的衰减权重,使其对当前时刻的参数估计产生连续性影响;最后,构建三级预警机制,并设计一种基于滑动窗口分析策略的自适应预警阈值调整方法,动态监测参数变化趋势,实时优化调整预警阈值。通过持续更新与校正不同参数的预警标准,提升了系统对异常形变的响应灵敏度与环境适应能力。基于真实矿区滑坡数据的试验结果表明,与传统固定阈值预警方法相比,该方法能够更早识别滑坡迹象并发出预警信号,在提升预警响应时效性的同时,在准确性方面亦表现出显著优势,有效增强了对滑坡风险的监测能力。更多还原

【Abstract】 Aiming at the issue that traditional slope landslide early warning methods for mining areas fail to effectively consider the influence of terrain characteristics on landslide processes, this study proposes an adaptive early warning threshold method based on dynamic time decay weight(DTDW). First, before processing radar image data, an automatic outlier detection and correction algorithm is applied to reduce data anomalies and enhance monitoring data quality. Next, the processed time-series radar deformation images are analyzed to extract the maximum deformation area as the study region, and multiple monitoring parameters(including velocity, acceleration, and coherence) within this area are calculated. Subsequently, the dynamic time decay weight(DTDW) is introduced, which assigns varying degrees of decay weights to deformation image parameters from historical moments, thereby enabling continuous influence on the parameter estimation at the current moment. Finally, a three-level warning mechanism is established,along with an adaptive warning threshold adjustment method based on a sliding window analysis strategy. This method dynamically monitors parameter trends and optimizes warning thresholds in real time. By continuously updating and calibrating warning criteria for different parameters, the system’s responsiveness to abnormal deformations and its adaptability to environmental changes are improved. Experimental results based on real mining area landslide data show that, compared with traditional fixed-threshold warning methods, the proposed approach can identify landslide signs earlier and issue warning signals more promptly. It demonstrates significant advantages in both timeliness and accuracy, effectively enhancing the monitoring capability for landslide risks.更多还原