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Digital close-range photogrammetric application to small-scale physical simulation experiment

中国有色金属学会会刊：英文版 2011年第S3期21卷 681-685页

作者： LI Chun-yi1, CUI Xi-min2. YU Yi-ju3.1. School of surveying and Landing Information Engineering, Henan Polytechnic University, Jiaozuo 454003. China 2. College of Geoscience and surveying Engineering, China University of Mining and Technology, {2. 100083. China {3., beijing 100045, China [a] School of surveying and Landing Information Engineering Henan Polytechnic University Jiaozuo 454003 China [b] College of Geoscience and surveying Engineering China University of Mining and Technology Beijing 100083 China [c] surveying and mapping{2. Beijing 100045 China

In order to research the possibility of digital close-range photogrammetric surveying in small scale physical simulation experiment, physical model coinciding with engineering practice was constructed based on similar theory. The datum processing method and surveying precision of digital close-range photogrammetric were analyzed. And the function relationship between overburden subsidence factor qr and the ratio z/H of stratum horizon z and mining depth H was researched. The results show that surveying points position mean error along horizontal direction is ±0.13. mm and vertical direction is ±0.192.mm. Therefore, multi-taking station cross direction digital close-range photogrammetric can completely satisfy the precision need of physical simulation experiment. And the empirical formula can be utilized to represent evolution law of stratum subsidence factor.

关键词： close-range photogrammetric physical simulation light-rays adjustment surveying precision subsidence factor

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The Mathematic Models of the Kalman Filtering for Across-Fault Measurement

引用

Earthquake Research in China 1994年第3期8卷 92-103页

作者： You Lilan,Liu Dajie,Huang Jia’na,Liu Xue and Zhou KechangInstitute of Crustat Dynamics,SSB,beijing 100085,China Wuhan Technical University of surveying and{2.,Wuhan 43.070,China National Center for Seismic Data and Inforraanon,SSB,beijing 100045,China

This paper makes a probe into the application of the Kalman filtering method to the data processing of across-fault *** the basis of statistical regression,the mathematic and stochastic models of filtration are established by combining the regression method with Kalman *** the filtering computation,not only the randomness of fault movements but also the time-dependent variation of environmental effects have been taken into *** use of the adaptive filtering method,an estimation of the dynamic noise variance matrix is obtained through *** for one measuring line(leveling line or baseline),two measuring lines(both leveling lines or both baselines)and four measuring lines(two leveling lines and two baselines)are derived and established *** means of these models,the data of across-fault measurements can be processed dynamically in real-time to provide the filtered values of height difference between benchmarks or baseline length at different time

关键词： Across-fault measurement Kalman filtration State equation Observational equation Initial state Dynamic noise

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