A fast algorithm based on the grayscale distribution of infrared target and the weighted kernel function was proposed for the moving target detection(MTD) in dynamic scene of image series. This algorithm is used to de...A fast algorithm based on the grayscale distribution of infrared target and the weighted kernel function was proposed for the moving target detection(MTD) in dynamic scene of image series. This algorithm is used to deal with issues like the large computational complexity, the fluctuation of grayscale, and the noise in infrared images. Four characteristic points were selected by analyzing the grayscale distribution in infrared image, of which the series was quickly matched with an affine transformation model. The image was then divided into 32×32 squares and the gray-weighted kernel(GWK) for each square was calculated. At last, the MTD was carried out according to the variation of the four GWKs. The results indicate that the MTD can be achieved in real time using the algorithm with the fluctuations of grayscale and noise can be effectively suppressed. The detection probability is greater than 90% with the false alarm rate lower than 5% when the calculation time is less than 40 ms.展开更多
The flow behavior in porous media with threshold pressure gradient(TPG) is more complex than Darcy flow and the equations of motion, and outer boundary and inner boundary with TPG are also different from Darcy flow fo...The flow behavior in porous media with threshold pressure gradient(TPG) is more complex than Darcy flow and the equations of motion, and outer boundary and inner boundary with TPG are also different from Darcy flow for unsteady flow of a producing well in a reservoir. An analytic method to solve this kind of problem is in a need of reestablishment. The classical method of Green's function and Newman product principle in a new way are used to solve the unsteady state flow problems of various shapes of well and reservoir while considering the TPG. Four Green's functions of point, line, band and circle while considering the TPG are achieved. Then, two well models of vertical well and horizontal well are built and simultaneously the function to calculate the moving boundary of each well model is provided. The results show that when considering TPG the pressure field is much different, which has a sudden pressure change, with a moving boundary in it. And the moving boundary of each well model increases with time but slows down rapidly, especially when the TGP is large.展开更多
为提升chirplet变换(chirplet transform,CT)估算瞬时频率的精度,在CT基础上结合花斑翠鸟优化(pied kingfisher optimizer,PKO)和径向基移动最小二乘(radial basis function moving least squares,RBFMLS)算法提出了一种识别结构瞬时频...为提升chirplet变换(chirplet transform,CT)估算瞬时频率的精度,在CT基础上结合花斑翠鸟优化(pied kingfisher optimizer,PKO)和径向基移动最小二乘(radial basis function moving least squares,RBFMLS)算法提出了一种识别结构瞬时频率的新方法。该方法采用正定紧支径向基函数作为移动最小二乘近似的权函数,对CT的能量脊线进行估算,同时应用PKO对RBFMLS节点支撑半径和CT窗函数宽度进行优化。通过一组解析信号数值算例和一个时变拉索试验验证了所提方法的有效性。研究结果表明,该方法能有效改善信号分析的能量聚集性,提高瞬时频率的识别精度。展开更多
基金Project(61101185)supported by the National Natural Science Foundation of China
文摘A fast algorithm based on the grayscale distribution of infrared target and the weighted kernel function was proposed for the moving target detection(MTD) in dynamic scene of image series. This algorithm is used to deal with issues like the large computational complexity, the fluctuation of grayscale, and the noise in infrared images. Four characteristic points were selected by analyzing the grayscale distribution in infrared image, of which the series was quickly matched with an affine transformation model. The image was then divided into 32×32 squares and the gray-weighted kernel(GWK) for each square was calculated. At last, the MTD was carried out according to the variation of the four GWKs. The results indicate that the MTD can be achieved in real time using the algorithm with the fluctuations of grayscale and noise can be effectively suppressed. The detection probability is greater than 90% with the false alarm rate lower than 5% when the calculation time is less than 40 ms.
基金Project(51304220) supported by the National Natural Science Foundation of ChinaProject(3144033) supported by the Beijing Natural Science Foundation,ChinaProject(20130007120014) supported by the Specialized Research Fund for the Doctoral Program of Higher Education of China
文摘The flow behavior in porous media with threshold pressure gradient(TPG) is more complex than Darcy flow and the equations of motion, and outer boundary and inner boundary with TPG are also different from Darcy flow for unsteady flow of a producing well in a reservoir. An analytic method to solve this kind of problem is in a need of reestablishment. The classical method of Green's function and Newman product principle in a new way are used to solve the unsteady state flow problems of various shapes of well and reservoir while considering the TPG. Four Green's functions of point, line, band and circle while considering the TPG are achieved. Then, two well models of vertical well and horizontal well are built and simultaneously the function to calculate the moving boundary of each well model is provided. The results show that when considering TPG the pressure field is much different, which has a sudden pressure change, with a moving boundary in it. And the moving boundary of each well model increases with time but slows down rapidly, especially when the TGP is large.
文摘为提升chirplet变换(chirplet transform,CT)估算瞬时频率的精度,在CT基础上结合花斑翠鸟优化(pied kingfisher optimizer,PKO)和径向基移动最小二乘(radial basis function moving least squares,RBFMLS)算法提出了一种识别结构瞬时频率的新方法。该方法采用正定紧支径向基函数作为移动最小二乘近似的权函数,对CT的能量脊线进行估算,同时应用PKO对RBFMLS节点支撑半径和CT窗函数宽度进行优化。通过一组解析信号数值算例和一个时变拉索试验验证了所提方法的有效性。研究结果表明,该方法能有效改善信号分析的能量聚集性,提高瞬时频率的识别精度。
