In the construction and maintenance of particle accelerators,all the accelerator elements should be installed in the same coordinate system,only in this way could the devices in the actual world be consistent with the...In the construction and maintenance of particle accelerators,all the accelerator elements should be installed in the same coordinate system,only in this way could the devices in the actual world be consistent with the design drawings.However,with the occurrence of the movements of the reinforced concrete cover plates at short notice or building deformations in the long term,the control points upon the engineering structure will be displaced,and the fitness between the subnetwork and the global control network may be irresponsible.Therefore,it is necessary to evaluate the deformations of the 3D alignment control network.Different from the extant investigations,in this paper,to characterize the deformations of the control network,all of the congruent models between the points measured in different epochs have been identified,and the congruence model with the most control points is considered as the primary or fundamental model,the remaining models are recognized as the additional ones.Furthermore,the discrepancies between the primary S-transformation parameters and the additional S-transformation parameters can reflect the relative movements of the additional congruence models.Both the iterative GCT method and the iterative combinatorial theory are proposed to detect multiple congruence models in the control network.Considering the actual work of the alignment,it is essential to identify the competitive models in the monitoring network,which can provide us a hint that,even the fitness between the subnetwork and the global control network is good,there are still deformations which may be ignored.The numerical experiments show that the suggested approaches can describe the deformation of the 3D alignment control network roundly.展开更多
The recent proliferation of the 3D reflection seismic method into the near-surface area of geophysical applications, especially in response to the emergence of the need to comprehensively characterize and monitor near...The recent proliferation of the 3D reflection seismic method into the near-surface area of geophysical applications, especially in response to the emergence of the need to comprehensively characterize and monitor near-surface carbon dioxide sequestration in shallow saline aquifers around the world, justifies the emphasis on cost-effective and robust quality control and assurance （QC/QA） workflow of 3D seismic data preprocessing that is suitable for near-surface applications. The main purpose of our seismic data preprocessing QC is to enable the use of appropriate header information, data that are free of noise-dominated traces, and/or flawed vertical stacking in subsequent processing steps. In this article, I provide an account of utilizing survey design specifications, noise properties, first breaks, and normal moveout for rapid and thorough graphical QC/QA diagnostics, which are easy to apply and efficient in the diagnosis of inconsistencies. A correlated vibroseis time-lapse 3D-seismic data set from a CO2-flood monitoring survey is used for demonstrating QC diagnostics. An important by-product of the QC workflow is establishing the number of layers for a refraction statics model in a data-driven graphical manner that capitalizes on the spatial coverage of the 3D seismic data.展开更多
In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfa...In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfaces represented by two actuated and un-actuated subsystems in the bridge crane. Parameters of the controller are then intelligently estimated, where uncertain parameters due to disturbances in the 3D overhead crane dynamic model are proposed to be represented by radial basis function networks whose weights are derived from a Lyapunov function. The proposed approach allows the crane system to be robust under uncertainty conditions in which some uncertain and unknown parameters are highly difficult to determine. Moreover, stability of the sliding surfaces is proved to be guaranteed. Effectiveness of the proposed approach is then demonstrated by implementing the algorithm in both synthetic and reallife systems, where the results obtained by our method are highly promising.展开更多
【目的】解决钢箱系杆拱桥的钢拱肋在施工过程中精度控制难度大和耗时长的问题。【方法】以某钢箱系杆拱桥为工程背景,采用建筑信息模型(building information modeling,BIM)及3D激光扫描技术,对拱肋钢构件在加工制作与拼接过程中的质...【目的】解决钢箱系杆拱桥的钢拱肋在施工过程中精度控制难度大和耗时长的问题。【方法】以某钢箱系杆拱桥为工程背景,采用建筑信息模型(building information modeling,BIM)及3D激光扫描技术,对拱肋钢构件在加工制作与拼接过程中的质量检测进行信息化管控。【结果】BIM技术结合3D激光扫描技术可快速地检测钢拱肋构件的质量并监测拱肋施工线形;钢箱拱肋构件的最大制作误差在1.2 mm以内,构件在拼接过程中的最大误差在1.1 mm以内,以上误差均满足设计规范的要求;与传统检测方法相比,点云数据在各坐标轴方向的偏差为1.0~3.0 mm,平均偏差为1.2~1.5 mm,具有较高的可靠性。【结论】基于BIM+3D激光扫描技术,可实现钢箱拱肋构件施工过程中拱肋线形质量的动态管控。展开更多
人脸重演技术作为可控人脸生成领域的关键研究方向,其目标在于通过给定的驱动人脸图像或视频帧,驱动源人脸图像,实现其面部表情和姿态的准确可控合成。该技术要求生成结果既能保持源人脸图像的身份特征,又能与驱动人脸图像的表情姿态保...人脸重演技术作为可控人脸生成领域的关键研究方向,其目标在于通过给定的驱动人脸图像或视频帧,驱动源人脸图像,实现其面部表情和姿态的准确可控合成。该技术要求生成结果既能保持源人脸图像的身份特征,又能与驱动人脸图像的表情姿态保持高度一致。单样本人脸重演任务由于仅依赖单一视角的2D人脸图像,导致面部信息描述不充分。现有方法在生成姿态变化幅度较大的人脸图像时,难以准确地保持人脸身份、表情姿态的一致性。针对该问题,提出了一种基于3D可解释性神经渲染的单样本人脸重演(3D Explainable Neural Rendering Based Single-sample Face Reenactment,3D-ENS)方法。该方法在神经网络内部显式建模出固定的3D人脸结构及纹理信息用于整个重演视频生成阶段,以保证重演结果中人脸身份的一致性和表情姿态变化的稳定性。在此基础上构建了一种神经纹理补全网络,通过多尺度特征学习机制实现高质量面部纹理重建;提出了一种背景运动估计网络,预测驱动后人脸图像的背景,将背景信息与补全后的面部神经纹理渲染(Neural Texture Rendering,NTR)结果进行融合。使用关键点检测模型提供面部一致性约束,进一步提升模型的表观一致性。在主流基准数据集与真实场景数据上的实验证明,所提方法具有较好的身份保持度,能够有效应对面部姿态变化的复杂场景,为人脸重演任务提供了新的解决方案。展开更多
文摘In the construction and maintenance of particle accelerators,all the accelerator elements should be installed in the same coordinate system,only in this way could the devices in the actual world be consistent with the design drawings.However,with the occurrence of the movements of the reinforced concrete cover plates at short notice or building deformations in the long term,the control points upon the engineering structure will be displaced,and the fitness between the subnetwork and the global control network may be irresponsible.Therefore,it is necessary to evaluate the deformations of the 3D alignment control network.Different from the extant investigations,in this paper,to characterize the deformations of the control network,all of the congruent models between the points measured in different epochs have been identified,and the congruence model with the most control points is considered as the primary or fundamental model,the remaining models are recognized as the additional ones.Furthermore,the discrepancies between the primary S-transformation parameters and the additional S-transformation parameters can reflect the relative movements of the additional congruence models.Both the iterative GCT method and the iterative combinatorial theory are proposed to detect multiple congruence models in the control network.Considering the actual work of the alignment,it is essential to identify the competitive models in the monitoring network,which can provide us a hint that,even the fitness between the subnetwork and the global control network is good,there are still deformations which may be ignored.The numerical experiments show that the suggested approaches can describe the deformation of the 3D alignment control network roundly.
基金supported by the U.S. Department of Energy (No. DE-FC26-03NT15414)
文摘The recent proliferation of the 3D reflection seismic method into the near-surface area of geophysical applications, especially in response to the emergence of the need to comprehensively characterize and monitor near-surface carbon dioxide sequestration in shallow saline aquifers around the world, justifies the emphasis on cost-effective and robust quality control and assurance （QC/QA） workflow of 3D seismic data preprocessing that is suitable for near-surface applications. The main purpose of our seismic data preprocessing QC is to enable the use of appropriate header information, data that are free of noise-dominated traces, and/or flawed vertical stacking in subsequent processing steps. In this article, I provide an account of utilizing survey design specifications, noise properties, first breaks, and normal moveout for rapid and thorough graphical QC/QA diagnostics, which are easy to apply and efficient in the diagnosis of inconsistencies. A correlated vibroseis time-lapse 3D-seismic data set from a CO2-flood monitoring survey is used for demonstrating QC diagnostics. An important by-product of the QC workflow is establishing the number of layers for a refraction statics model in a data-driven graphical manner that capitalizes on the spatial coverage of the 3D seismic data.
文摘In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfaces represented by two actuated and un-actuated subsystems in the bridge crane. Parameters of the controller are then intelligently estimated, where uncertain parameters due to disturbances in the 3D overhead crane dynamic model are proposed to be represented by radial basis function networks whose weights are derived from a Lyapunov function. The proposed approach allows the crane system to be robust under uncertainty conditions in which some uncertain and unknown parameters are highly difficult to determine. Moreover, stability of the sliding surfaces is proved to be guaranteed. Effectiveness of the proposed approach is then demonstrated by implementing the algorithm in both synthetic and reallife systems, where the results obtained by our method are highly promising.
文摘人脸重演技术作为可控人脸生成领域的关键研究方向,其目标在于通过给定的驱动人脸图像或视频帧,驱动源人脸图像,实现其面部表情和姿态的准确可控合成。该技术要求生成结果既能保持源人脸图像的身份特征,又能与驱动人脸图像的表情姿态保持高度一致。单样本人脸重演任务由于仅依赖单一视角的2D人脸图像,导致面部信息描述不充分。现有方法在生成姿态变化幅度较大的人脸图像时,难以准确地保持人脸身份、表情姿态的一致性。针对该问题,提出了一种基于3D可解释性神经渲染的单样本人脸重演(3D Explainable Neural Rendering Based Single-sample Face Reenactment,3D-ENS)方法。该方法在神经网络内部显式建模出固定的3D人脸结构及纹理信息用于整个重演视频生成阶段,以保证重演结果中人脸身份的一致性和表情姿态变化的稳定性。在此基础上构建了一种神经纹理补全网络,通过多尺度特征学习机制实现高质量面部纹理重建;提出了一种背景运动估计网络,预测驱动后人脸图像的背景,将背景信息与补全后的面部神经纹理渲染(Neural Texture Rendering,NTR)结果进行融合。使用关键点检测模型提供面部一致性约束,进一步提升模型的表观一致性。在主流基准数据集与真实场景数据上的实验证明,所提方法具有较好的身份保持度,能够有效应对面部姿态变化的复杂场景,为人脸重演任务提供了新的解决方案。
