自成孔预应力锚杆研究与应用

自成孔预应力锚杆属于土层锚杆的一种,通过将荷载传递至周围岩土层中而提供拉拔力。结合自成孔钻头及工艺要求,给出了一般施工方法。基于对荷载传递机理的认识,借助于承载体,该施工方法可以推广应用于荷载分散型锚杆的施工。根据3个压力分散型自成孔预应力锚杆的现场原位拉拔试验,表明其极限拉拔力可达800～1000 kN,进而说明自成孔预应力锚杆体系的可靠性,并可在基坑工程中进一步应用。

自成孔预应力锚杆在深基坑围护中的应用

在深基坑围护结构设计中,在地质条件合适的大面积的基坑采用自成孔预应力土锚杆围护结构,较之内支撑系统具有开挖工作面开阔、工期较短、造价较低和工程结束时不必拆撑等优点。在此通过工程实例叙述自成孔预应力锚杆的构造、施工工艺流程、施工要点和质量保证措施。

PHASE AUTOFOCUSING ALGORITHM FOR COMPRESSED INVERSE SYNTHETIC APERTURE RADAR IMAGING

As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A phase autofocusing algorithm for compressed ISAR imaging is presented. In the algorithm, phase autofocusing for the sparse ISAR echoes is accomplished using the eigenvector method. Experimental results validate the effectiveness of the algorithm.

Entropy function optimization for radar imaging

The convergence performance of the minimum entropy auto-focusing（MEA） algorithm for inverse synthetic aperture radar（ISAR） imaging is analyzed by simulation. The results show that a local optimal solution problem exists in the MEA algorithm. The cost function of the MEA algorithm is not a downward-convex function of multidimensional phases to be compensated. Only when the initial values of the compensated phases are chosen to be near the global minimal point of the entropy function, the MEA algorithm can converge to a global optimal solution. To study the optimal solution problem of the MEA algorithm, a new scheme of entropy function optimization for radar imaging is presented. First, the initial values of the compensated phases are estimated by using the modified Doppler centroid tracking （DCT）algorithm. Since these values are obtained according to the maximum likelihood （ML） principle, the initial phases can be located near the optimal solution values. Then, a fast MEA algorithm is used for the local searching process and the global optimal solution can be obtained. The simulation results show that this scheme can realize the global optimization of the MEA algorithm and can avoid the selection and adjustment of parameters such as iteration step lengths, threshold values, etc.

ADAPTIVE RIVER SEGMENTATION IN SAR IMAGES

There is difficulty for distinguishing of river and shadow in Synthetic Aperture Radar (SAR) images. A method of river segmentation in SAR images based on wavelet energy and gradient is proposed in this paper. It mainly includes two algorithms: coarse segmentation and refined segmen- tation. Firstly, The river regions are coarsely segmented by the wavelet energy feature,and then refined segmented accurately by the gradient threshold which is got adaptively. The experimental results show the validity of the method, which provides a good foundation for targets detection above the river.

THE REALIZATION OF THE PPP AUTOFOCUS METHOD IN PFA FOR SPOTLIGHT MODE SAR IMAGING

This paper first studies the phase errors for fine-resolution spotlight mode SAR imaging and decomposes the phase errors into two kinds, one is caused by translation and the other by rotation. Mathematical analysis and computer simulations show the above mentioned motion kinds and their corresponding damages on spotlight mode SAR imaging. Based on this analysis, a single PPP is introduced for spotlight mode SAR imaging with the PFA on the assumption that relative rotation between APC and imaged scene is uniform. The selected single point is used first to correct the quadratic and higher order phase errors and then to adjust the linear errors. After this compensation, the space-invariant phase errors caused by translation are almost corrected. Finally results are presented with the simulated data.

Extracting Eco-hydrological Information of Inland Wetland from L-band Synthetic Aperture Radar Image in Honghe National Nature Reserve, Northeast China

Taking a typical inland wetland of Honghe National Nature Reserve (HNNR), Northeast China, as the study area, this paper studied the application of L-band Synthetic Aperture Radar (SAR) image in extracting eco-hydrological information of inland wetland. Landsat-5 TM and ALOS PALSAR HH backscatter images were first fused by using the wavelet-IHS method. Based on the fused image data, the classification method of support vector machines was used to map the wetland in the study area. The overall mapping accuracy is 77.5%. Then, the wet and dry aboveground biomass estimation models, including statistical models and a Rice Cloudy model, were established. Optimal parameters for the Rice Cloudy model were calculated in MATLAB by using the least squares method. Based on the validation results, it was found that the Rice Cloudy model produced higher accuracy for both wet and dry aboveground biomass estimation compared to the statistical models. Finally, subcanopy water boundary information was extracted from the HH backscatter image by threshold method. Compared to the actual water borderline result, the extracted result from L-band SAR image is reliable. In this paper, the HH-HV phase difference was proved to be valueless for extracting subcanopy water boundary information.

Symmetry-breaking assembled porous calcite microspheres and their multiple dental applications

Biomedical applications of porous calcium car- bonate （CaCO3） microspheres have been mainly restricted by their aqueous instability and low remineralization rate. To overcome these obstacles, a novel symmetry-breaking assembled porous calcite microsphere （PCMS） was con- structed in an ethanol/water mixed system using a two-step vapor-diffusion/aging crystallization strategy. In contrast to the conventional additive-induced crystallization method, the present strategy was performed under mild conditions and was free from any foreign additives, thus avoiding the potential contamination of the final product. Meanwhile, the prepared PCMSs were characterized by their highly uniform spherical morphology and large open pores, which are fa- vorable for large protein delivery. An antimicrobial study of immunoglobulin Y （IgY）-loaded PCMSs revealed excellent antimicrobial activity against Streptococcus mutans. More importantly, they showed surprisingly rapid transformation to bone minerals in physiological medium. Evaluation of the in vitro efficacy of PCMSs in dentinal tubule occlusion demonstrated their powerful potential to serve as a catalyst in the repair of dental hard tissue. Therefore, the developed PCMSs show great promise as multifunctional biomaterials for dental treatment applications.

A feature extraction method for synthetic aperture radar(SAR) automatic target recognition based on maximum interclass distance

Synthetic aperture radar(SAR) automatic target recognition is an important application in SAR.How to extract features has restricted the application of SAR technology seriously.In this paper,a new feature extraction method for SAR automatic target recognition based on maximum interclass distance is proposed,which integrates class and neighborhood information.This method can reinforce discriminative power using maximum interclass distance,so it can improve recognition rate effectively.

A multiphase texture segmentation method based on local intensity distribution and Potts model

Because texture images cannot be directly processed by the gray level information of individual pixel,we propose a new texture descriptor which reflects the intensity distribution of the patch centered at each pixel.Then the general multiphase image segmentation model of Potts model is extended for texture segmentation by adding the region information of the texture descriptor.A fast numerical scheme based on the split Bregman method is designed to speed up the computational process.The algorithm is efficient,and both the texture descriptor and the characteristic functions can be implemented easily.Experiments using synthetic texture images,real natural scene images and synthetic aperture radar images are presented to give qualitative comparisons between our method and other state-of-the-art techniques.The results show that our method can accurately segment object regions and is competitive compared with other methods especially in segmenting natural images.