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Development of a new inversion method for detecting spatiotemporal characteristics of coal mines based on earth observation technology
International Journal of Applied Earth Observation and Geoinformation ( IF 7.6 ) Pub Date : 2021-04-25 , DOI: 10.1016/j.jag.2021.102346
Lei Wang , Kegui Jiang , Tao Wei

We propose a novel methodology for detecting the spatiotemporal characteristics of coal mines based on earth observation technology. Based on the dynamic probability integral model, the spatiotemporal relationship model between underground mining and ground surface response is constructed by fitting dynamic probability integral parameters. Considering the highly non-linearity of the constructed model, an improved fireworks algorithm (IFWA) is introduced to solve the target parameters. Taking the surface above a specific working panel of Guqiao Coal Mine in Huainan, China as the experimental area, based on the short-term surface monitoring data of the observation station, the proposed method was applied to detect the spatiotemporal characteristics of underground mining in six periods. The results show that the detected spatiotemporal characteristics were consistent with the measured ones. However, the large fluctuation of the dynamic probability integral parameters, and subcritical extraction may affect the method. In the simulation experiment, the model error of the construction method for multiple periods obtained was in the range of 0–21.0%, with an average of 5.0%. Furthermore, the sensitivity of the inverted spatiotemporal characteristic parameters to the input probability integral parameters was studied, and the results show that when error percentages of less than 20%, the inversion of target parameters are closer to the simulation (the mean relative errors is approximately 7.7%). Due to the advantages of short-term earth observation, this study provides a practical, convenient method for detecting spatiotemporal characteristics of underground mining, and avoids time-consuming and laborious long-term monitoring.



中文翻译:

基于地球观测技术的煤矿时空特征反演新方法的研制

我们提出了一种基于地球观测技术的煤矿时空特征检测新方法。基于动态概率积分模型,通过拟合动态概率积分参数,建立了地下采矿与地表响应的时空关系模型。考虑到所构建模型的高度非线性,引入了一种改进的烟花算法(IFWA)来求解目标参数。以淮南市古桥煤矿特定工作面板上方的地表为实验区域,基于观测站的短期地面监测数据,将所提出的方法应用于6个地下矿山的时空特征检测。时期。结果表明,所测时空特征与实测时空特征一致。但是,动态概率积分参数的较大波动以及亚临界提取可能会影响该方法。在模拟实验中,多次获得的构造方法的模型误差在0–21.0%的范围内,平均为5.0%。此外,研究了反时空特征参数对输入概率积分参数的敏感性,结果表明,当误差百分比小于20%时,目标参数的反演更接近于模拟(平均相对误差约为7.7%)。由于短期地球观测的优势,这项研究提供了一种实用的,

更新日期:2021-04-26
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