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Early Warning and Prediction Approach Based on Ground-Based SAR Data
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Yuxi LIU1, Fengyun YANG1, Hongnan QIN2
Mining and Metallurgical Engineering | 2023, 43(3) : 33 - 37
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Mining and Metallurgical Engineering | 2023, 43(3): 33-37
• MINING •
Early Warning and Prediction Approach Based on Ground-Based SAR Data
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Yuxi LIU1, Fengyun YANG1, Hongnan QIN2
Affiliations
  • 1.School of Civil Engineering, Liaoning University of Science and Technology, Anshan 114051, Liaoning, China
  • 2.China Academy of Safety Science & Technology, Beijing 100012, China
Published: 2023-06-01 doi: 10.3969/j.issn.0253-6099.2023.03.008
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In view of the data of ground-based SAR presenting high oscillation and high fluctuation with less obvious characteristic trend, an approach for early warning and prediction of slope deformation by using velocity reciprocity was proposed, which adopts a data processing method of subtracting dislocations and deleting limits to optimize the quality of deformation data, thus the accuracy of early warning and timely prediction of landslide can be improved. The application of this approach in an iron mine in Inner Mongolia shows that not only those problems faced in the actual actuation can be solved, but also the data about disaster approaching can present obvious deformation rule. It is concluded that this early warming and prediction approach has a wide application.

mine geological disasters  /  geological hazard monitoring  /  landslide  /  ground-based SAR  /  early warning  /  prediction  /  mine safety  /  landslide
Yuxi LIU, Fengyun YANG, Hongnan QIN. Early Warning and Prediction Approach Based on Ground-Based SAR Data[J]. Mining and Metallurgical Engineering, 2023 , 43 (3) : 33 -37 . DOI: 10.3969/j.issn.0253-6099.2023.03.008
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Year 2023 volume 43 Issue 3
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Article Info
doi: 10.3969/j.issn.0253-6099.2023.03.008
  • Receive Date：2023-01-02
  • Online Date：2026-03-05
  • Published：2023-06-01
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  • Received：2023-01-02
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Affiliations
    1.School of Civil Engineering, Liaoning University of Science and Technology, Anshan 114051, Liaoning, China
    2.China Academy of Safety Science & Technology, Beijing 100012, China
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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