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地震前兆数据异常自动检测报警系统 总被引:2,自引:0,他引:2
通过对地震前兆数据的分析与研究,研制了一套地震前兆数据异常自动检测与报警系统.该系统可实现测项分量与检测方法的自由定制,通过利用相关分析、差分检测、固体潮相关检测、方差检测、台阶检测与金日光第四统计力学群子统计理论等多种检测方法,实现了对数据的自动异常检测与报警.试验证明,该系统有效可行,可为地震数据监测人员与地震预报... 相似文献
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本文对积分安培离子色谱法测定地下水中碘化物含量的不确定度进行了评定,标准曲线采用双误差拟合法,建立了不确定度评定模型,得出几种影响测定结果的因素。 相似文献
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根据Chapman理论模型,在各向异性介质(如HTI介质)中,当入射角在0-45。范围内,慢横波会发生较大的衰减和频散,且对流体粘度敏感,而P波和快横波则比较小。对于沿裂隙法向传播的慢横波,其振幅受流体影响很大。因此,在P波响应对流体不敏感的情况下,可利用慢横波来获得裂隙型油气藏的流体信息。本文分析了胜利油田垦71地区三维三分量地震数据,检测出的慢横波振幅和旅行时异常与该区的测井资料十分吻合。分析结果还发现,与含油区相比,含水区会产生更高的横波分裂。在含水区,慢横波振幅会产生明显变化,而在含油区则几乎没有变化。 相似文献
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Oil spill detection with fully polarimetric UAVSAR data 总被引:3,自引:0,他引:3
In this study, two ocean oil spill detection approaches based on four scattering matrices measured by fully polarimetric synthetic aperture radar (SAR) are presented and compared. The first algorithm is based on the co-polar correlation coefficient, ρ, and the scattering matrix decomposition parameters, Cloud entropy (H), mean scattering angle (α) and anisotropy (A). While each of these parameters has oil spill signature in it, we find that combining these parameters into a new parameter, F, is a more effective way for oil slick detection. The second algorithm uses the total power of four polarimetric channels image (SPAN) to find the optimal representation of the oil spill signature. Otsu image segmentation method can then be applied to the F and SPAN images to extract the oil slick features. Using the L-band fully polarimetric Uninhabited Aerial Vehicle – synthetic aperture radar (UAVSAR) data acquired during the 2010 Deepwater Horizon oil spill disaster event in the Gulf of Mexico, we are able to successfully extract the oil slick information in the contaminated ocean area. Our result shows that both algorithms perform well in identifying oil slicks in this case. 相似文献
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Peter Schürch Alexander L. Densmore Nicholas J. Rosser Michael Lim Brian W. McArdell 《地球表面变化过程与地形》2011,36(14):1847-1859
Detection of surface change is a fundamental task in geomorphology. Terrestrial laser scanners are increasingly used for monitoring surface change resulting from a variety of geomorphic processes, as they allow the rapid generation of high‐resolution digital elevation models. Irrespective of instrument specifics, survey design or data processing, such data are subject to a finite level of ambiguity in position measurement, a consideration of which must be taken into account when deriving change. The propagation of errors is crucial in change detection because even very small uncertainties in elevation can produce large uncertainties in volume when extrapolated over an area of interest. In this study we propose a methodology to detect surface change and to quantify the resultant volumetric errors in areas of complex topography such as channels, where data from multiple scan stations must be combined. We find that a commonly proposed source of error – laser point elongation at low incidence angles – has a negligible effect on the quality of the final registered point cloud. Instead, ambiguities in elevation inherent to registered datasets have a strong effect on our ability to detect and measure surface change. Similarly, we find that changes in surface roughness between surveys also reduce our ability to detect change. Explicit consideration of these ambiguities, when propagated through to volume calculations, allows us to detect volume change of 87 ± 5 m3, over an area of ~ ?4900 m2, due to passage of a debris flow down a 300 m reach of the Illgraben channel in Switzerland. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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