In order to research start-up pressure wave propagation mechanism and determine pressure wave speed in gelled crude oil pipelines accurately,experiment of Large-scale flow loop was carried out.In the experiment,start-...In order to research start-up pressure wave propagation mechanism and determine pressure wave speed in gelled crude oil pipelines accurately,experiment of Large-scale flow loop was carried out.In the experiment,start-up pressure wave speeds under various operation conditions were measured,and effects of correlative factors on pressure wave were analyzed.The experimental and theoretical analysis shows that thermal shrinkage and structural properties of gelled crude oils are key factors influencing on start-up pressure wave propagation.The quantitative analysis for these effects can be done by using volume expansion coefficient and structural property parameter of gelled crude oil.A new calculation model of pressure wave speed was developed on the basis of Large-scale flow loop experiment and theoretical analysis.展开更多
Stable local feature detection is a fundamental component of many stereo vision problems such as 3-D reconstruction, object localization, and object tracking. A robust method for extracting scale-invariant feature poi...Stable local feature detection is a fundamental component of many stereo vision problems such as 3-D reconstruction, object localization, and object tracking. A robust method for extracting scale-invariant feature points is presented. First, the Harris corners in three-level pyramid are extracted. Then, the points detected at the highest level of the pyramid are correctly propagated to the lower level by pyramid based scale invariant （PBSI） method. The corners detected repeatedly in different levels are chosen as final feature points. Finally, the characteristic scale is obtained based on maximum entropy method. The experimental results show that the algorithm has low computation cost, strong antinoise capability, and excellent performance in the presence of significant scale changes.展开更多
基金Project(2008B-2901) supported by China National Petroleum Corporation
文摘In order to research start-up pressure wave propagation mechanism and determine pressure wave speed in gelled crude oil pipelines accurately,experiment of Large-scale flow loop was carried out.In the experiment,start-up pressure wave speeds under various operation conditions were measured,and effects of correlative factors on pressure wave were analyzed.The experimental and theoretical analysis shows that thermal shrinkage and structural properties of gelled crude oils are key factors influencing on start-up pressure wave propagation.The quantitative analysis for these effects can be done by using volume expansion coefficient and structural property parameter of gelled crude oil.A new calculation model of pressure wave speed was developed on the basis of Large-scale flow loop experiment and theoretical analysis.
文摘依据FFT→优化窗→IFFT思路,突破线性时频变换的窗函数积分性能桎梏,实现高性能优化窗函数的线性时频变换应用,建立新型时频变换算法——K-S变换.对信号x(t)的FFT频谱向量进行频移处理后,与该频移点下Kaiser优化窗的频谱向量进行Hadamard乘积,再将乘积结果进行FFT逆变换(IFFT),构造出K-S变换复时频矩阵,由此获得x(t)的时间-频率-幅值、时间-频率-相位三维信息;给出逆变换的数学推导与局部性质、线性性质和变分辨率特性;0~150 kHz电网的稳态与时变超谐波信号仿真实验表明,K-S变换的时域、频域分辨能力均优于流行的短时傅里叶变换、S变换,具有优良的变分辨率性能;0~40 kHz超谐波信号的实测证明,基于K-S变换的超谐波电压幅值测量绝对误差均小于0.032 3 V.
基金supported by the Development Program of China and the National Science Foundation Project (60475024)National High Technology Research (2006AA09Z203)
文摘Stable local feature detection is a fundamental component of many stereo vision problems such as 3-D reconstruction, object localization, and object tracking. A robust method for extracting scale-invariant feature points is presented. First, the Harris corners in three-level pyramid are extracted. Then, the points detected at the highest level of the pyramid are correctly propagated to the lower level by pyramid based scale invariant （PBSI） method. The corners detected repeatedly in different levels are chosen as final feature points. Finally, the characteristic scale is obtained based on maximum entropy method. The experimental results show that the algorithm has low computation cost, strong antinoise capability, and excellent performance in the presence of significant scale changes.
