Denoising of full-tensor gravity-gradiometer data involves detailed information from field sources, especially the data mixed with high-frequency random noise. We present a denoising method based on the translation-in...Denoising of full-tensor gravity-gradiometer data involves detailed information from field sources, especially the data mixed with high-frequency random noise. We present a denoising method based on the translation-invariant wavelet with mixed thresholding and adaptive threshold to remove the random noise and retain the data details. The novel mixed thresholding approach is devised to filter the random noise based on the energy distribution of the wavelet coefficients corresponding to the signal and random noise. The translation- invariant wavelet suppresses pseudo-Gibbs phenomena, and the mixed thresholding better separates the wavelet coefficients than traditional thresholding. Adaptive Bayesian threshold is used to process the wavelet coefficients according to the specific characteristics of the wavelet coefficients at each decomposition scale. A two-dimensional discrete wavelet transform is used to denoise gridded data for better computational efficiency. The results of denoising model and real data suggest that compared with Gaussian regional filter, the proposed method suppresses the white Gaussian noise and preserves the high-frequency information in gravity-gradiometer data. Satisfactory denoising is achieved with the translation-invariant wavelet.展开更多
The distribution characteristics of rare earth elements （REE） in bottomsediments are influenced by many factors. Hence, conducting a quantitative analysis isdifficult. A qualitative analysis of the relationships bet...The distribution characteristics of rare earth elements （REE） in bottomsediments are influenced by many factors. Hence, conducting a quantitative analysis isdifficult. A qualitative analysis of the relationships between ΣREE content andprovenance, hydrodynamics, grain size and mineral distribution in the Beibu Gulf showsthat terrestrial rocks control the ΣREE composition. Both weaker hydrodynamics andfiner grain size lead to a higher ΣREE content. Relative curves revealing therelationships between individual impact factors and ΣREE content were obtained fromthe combination of qualitative and quantitative analyses of the BP neural network,which trained the position of samples, gravel content, sand content, silt content, claycontent and clay mineral content. The results are consistent with those of thequantitative analysis. The self-learning algorithm is automatically determined andcalculated quantitatively. The impact of each factor on REEs and how each factorcontrols the ΣREE distribution is identified. Thus, environmental changes and thegeological evolution of the region can be inferred based on curve variation and the geological evolution of the region can be inferred based on curve variation and theactual situation. This method also provides useful theoretical guidance for the analysisof REE enrichment and dispersion.展开更多
The construction of the bridge across Taiwan Strait has been studied for a long time and the feasibility study that has attracted attention among scientists and engineers on both sides of the Taiwan Strait[1-4].The ke...The construction of the bridge across Taiwan Strait has been studied for a long time and the feasibility study that has attracted attention among scientists and engineers on both sides of the Taiwan Strait[1-4].The key question is whether this bridge and dike-road across Taiwan Strait can be constructed with present technology under such complex geological conditions or not.The results of current researches indicate that the sea floor of the Strait is covered with a horizontal layer composed of both the Pleistocene and the Holocene sandstone and shale with a thickness of about 200~300m.The distance from Pingtan island to China's Xinzhu seashore is 124 km,which might be connected by 4-6 section bridges and 5-7 section of dike-roads,and serve as a best program of the route in the north Strait section.The NE offshore fault along the Fujian coast and that along the west coast of Taiwan,China are the major tectonic lines separated by several NW faults under the upper horizontal layer,these fault 3D feature may be detecting by geo-tomography technique,which can help to deal with the foundation of bridge and dike-road piers.It is judged that the construction of bridge and dike-road beginning from Pingtan to the China's Xinzhu seashore is worth recommendation.In the procedure of the construction of large and high height bridges,must consider the steel structural member be detected by industrial CT technology,and might detect the pier of bridge and dike-road which built by steel tube and reinforced concrete at dike-roads two side,in order to get the hard basement and getting the depth of the pier extend below the sea-floor by the seismic tomographic detection method.展开更多
基金supported by the National Key Research and Development Plan Issue(Nos.2017YFC0602203 and2017YFC0601606)the National Science and Technology Major Project Task(No.2016ZX05027-002-003)+4 种基金the National Natural Science Foundation of China(Nos.41604089 and 41404089)the State Key Program of National Natural Science of China(No.41430322)the Marine/Airborne Gravimeter Research Project(No.2011YQ12004505)the State Key Laboratory of Marine Geology,Tongji University(No.MGK1610)the Basic Scientific Research Business Special Fund Project of Second Institute of Oceanography,State Oceanic Administration(No.14275-10)
文摘Denoising of full-tensor gravity-gradiometer data involves detailed information from field sources, especially the data mixed with high-frequency random noise. We present a denoising method based on the translation-invariant wavelet with mixed thresholding and adaptive threshold to remove the random noise and retain the data details. The novel mixed thresholding approach is devised to filter the random noise based on the energy distribution of the wavelet coefficients corresponding to the signal and random noise. The translation- invariant wavelet suppresses pseudo-Gibbs phenomena, and the mixed thresholding better separates the wavelet coefficients than traditional thresholding. Adaptive Bayesian threshold is used to process the wavelet coefficients according to the specific characteristics of the wavelet coefficients at each decomposition scale. A two-dimensional discrete wavelet transform is used to denoise gridded data for better computational efficiency. The results of denoising model and real data suggest that compared with Gaussian regional filter, the proposed method suppresses the white Gaussian noise and preserves the high-frequency information in gravity-gradiometer data. Satisfactory denoising is achieved with the translation-invariant wavelet.
文摘The distribution characteristics of rare earth elements （REE） in bottomsediments are influenced by many factors. Hence, conducting a quantitative analysis isdifficult. A qualitative analysis of the relationships between ΣREE content andprovenance, hydrodynamics, grain size and mineral distribution in the Beibu Gulf showsthat terrestrial rocks control the ΣREE composition. Both weaker hydrodynamics andfiner grain size lead to a higher ΣREE content. Relative curves revealing therelationships between individual impact factors and ΣREE content were obtained fromthe combination of qualitative and quantitative analyses of the BP neural network,which trained the position of samples, gravel content, sand content, silt content, claycontent and clay mineral content. The results are consistent with those of thequantitative analysis. The self-learning algorithm is automatically determined andcalculated quantitatively. The impact of each factor on REEs and how each factorcontrols the ΣREE distribution is identified. Thus, environmental changes and thegeological evolution of the region can be inferred based on curve variation and the geological evolution of the region can be inferred based on curve variation and theactual situation. This method also provides useful theoretical guidance for the analysisof REE enrichment and dispersion.
文摘The construction of the bridge across Taiwan Strait has been studied for a long time and the feasibility study that has attracted attention among scientists and engineers on both sides of the Taiwan Strait[1-4].The key question is whether this bridge and dike-road across Taiwan Strait can be constructed with present technology under such complex geological conditions or not.The results of current researches indicate that the sea floor of the Strait is covered with a horizontal layer composed of both the Pleistocene and the Holocene sandstone and shale with a thickness of about 200~300m.The distance from Pingtan island to China's Xinzhu seashore is 124 km,which might be connected by 4-6 section bridges and 5-7 section of dike-roads,and serve as a best program of the route in the north Strait section.The NE offshore fault along the Fujian coast and that along the west coast of Taiwan,China are the major tectonic lines separated by several NW faults under the upper horizontal layer,these fault 3D feature may be detecting by geo-tomography technique,which can help to deal with the foundation of bridge and dike-road piers.It is judged that the construction of bridge and dike-road beginning from Pingtan to the China's Xinzhu seashore is worth recommendation.In the procedure of the construction of large and high height bridges,must consider the steel structural member be detected by industrial CT technology,and might detect the pier of bridge and dike-road which built by steel tube and reinforced concrete at dike-roads two side,in order to get the hard basement and getting the depth of the pier extend below the sea-floor by the seismic tomographic detection method.
