The efficiencies of 6 kinds of macromolecules with dendritic structure in improving the flow properties of crude oil were investigated. The dendritic additives were synthesized using low-generation dendritic poly(amid...The efficiencies of 6 kinds of macromolecules with dendritic structure in improving the flow properties of crude oil were investigated. The dendritic additives were synthesized using low-generation dendritic poly(amidoamine) and alkyl longchain acrylic esters as starting materials, and their structures were characterized by the Fourier transform infrared spectroscopy, 1H-nuclear magnetic resonance and elemental analysis. The effects on the pour point and rheological properties of crude oil samples were studied. Efficiencies of dendritic long-chain esters were not only influenced by the alky chain length, but also by the generation of dendrimer. The longer the alkyl chain of dendritic long-chain ester was, the better the effect in the reduction of pour point and apparent viscosity was. Efficiencies of 1.5 generation dendritic long-chain ester with 8 branched chains for the reduction of pour point and apparent viscosity were superior to those of 0.5 generation dendritic long-chain ester with 4 branched chains. Under the same conditions, efficiencies of 1.5 generation dendritic eighteen ester were superior to those of other 1.5 generation dendritic long-chain esters for the reduction of pour point and viscosity of crude oil.展开更多
For a vision measurement system consisted of laser-CCD scanning sensors, an algorithm is proposed to extract and recognize the target object contour. Firstly, the two-dimensional（2D） point cloud that is output by th...For a vision measurement system consisted of laser-CCD scanning sensors, an algorithm is proposed to extract and recognize the target object contour. Firstly, the two-dimensional（2D） point cloud that is output by the integrated laser sensor is transformed into a binary image. Secondly, the potential target object contours are segmented and extracted based on the connected domain labeling and adaptive corner detection. Then, the target object contour is recognized by improved Hu invariant moments and BP neural network classifier. Finally, we extract the point data of the target object contour through the reverse transformation from a binary image to a 2D point cloud. The experimental results show that the average recognition rate is 98.5% and the average recognition time is 0.18 s per frame. This algorithm realizes the real-time tracking of the target object in the complex background and the condition of multi-moving objects.展开更多
基金supported financially by the Heilongjiang Postdoctorial Financial Foundation of China (Project NO. LBH-Zo8290)The Daqing Oil Field of China was thanked for providing the financial support and the crude oil
文摘The efficiencies of 6 kinds of macromolecules with dendritic structure in improving the flow properties of crude oil were investigated. The dendritic additives were synthesized using low-generation dendritic poly(amidoamine) and alkyl longchain acrylic esters as starting materials, and their structures were characterized by the Fourier transform infrared spectroscopy, 1H-nuclear magnetic resonance and elemental analysis. The effects on the pour point and rheological properties of crude oil samples were studied. Efficiencies of dendritic long-chain esters were not only influenced by the alky chain length, but also by the generation of dendrimer. The longer the alkyl chain of dendritic long-chain ester was, the better the effect in the reduction of pour point and apparent viscosity was. Efficiencies of 1.5 generation dendritic long-chain ester with 8 branched chains for the reduction of pour point and apparent viscosity were superior to those of 0.5 generation dendritic long-chain ester with 4 branched chains. Under the same conditions, efficiencies of 1.5 generation dendritic eighteen ester were superior to those of other 1.5 generation dendritic long-chain esters for the reduction of pour point and viscosity of crude oil.
文摘For a vision measurement system consisted of laser-CCD scanning sensors, an algorithm is proposed to extract and recognize the target object contour. Firstly, the two-dimensional（2D） point cloud that is output by the integrated laser sensor is transformed into a binary image. Secondly, the potential target object contours are segmented and extracted based on the connected domain labeling and adaptive corner detection. Then, the target object contour is recognized by improved Hu invariant moments and BP neural network classifier. Finally, we extract the point data of the target object contour through the reverse transformation from a binary image to a 2D point cloud. The experimental results show that the average recognition rate is 98.5% and the average recognition time is 0.18 s per frame. This algorithm realizes the real-time tracking of the target object in the complex background and the condition of multi-moving objects.
