Based on plastic bending engineering theory and machine vision technology, the intelligent control technology for forming steel pipe with JCO process is presented in this paper. By ‘twice pre-bending method’ in the ...Based on plastic bending engineering theory and machine vision technology, the intelligent control technology for forming steel pipe with JCO process is presented in this paper. By ‘twice pre-bending method’ in the first forming step, the springback law can be obtained. With the springback law and the target angle, the exact punch displacement which determines the formed angle in each bending step is predicted. In the succedent forming steps, the bending process is carried out with the exact punch displacement by real-time revising the springback law. And the angle error in each forming step is calculated by comparing the actual formed angle with the target angle. By conducting compensation for the last angle error in the next forming step, each precise bending process step is realized. A system of intelligent control technology for forming the steel pipe was developed. A calibration method is proposed to calculate the exterior parameters of the CCD camera, in which the equilateral triangle is em-ployed as the calibrating board and only one image needs to be captured. A mathematical model, which converts the angle in the image into the actual formed angle, is derived. The experimental results showed that the ellipticity of the formed pipes was less than 1.5% and the high-quality pipes can be manufactured without the worker's operating experience by employing the in-telligent control technology.展开更多
In this paper, we have investigated the peristaltic flow of Williamson fluid in a curved channel. The governing equations of Williamson fluid model for curved channel are derived including the effects of curvature. Th...In this paper, we have investigated the peristaltic flow of Williamson fluid in a curved channel. The governing equations of Williamson fluid model for curved channel are derived including the effects of curvature. The highly nonlinear partial differential equa- tions are simplified by using the wave frame transformation, long wavelength and low Reynolds number assumptions. The reduced nonlinear partial differential equation is solved analytically with the help of homotopy perturbation method. The physical features of pertinent parameters have been discussed by plotting the graphs of pressure rise, velocity profile and stream functions.展开更多
基金Supported by the National Natural Science Foundation of China (Grant No. 50805126)the Hebei Natural Science Foundation (Grant No. E2009000389)
文摘Based on plastic bending engineering theory and machine vision technology, the intelligent control technology for forming steel pipe with JCO process is presented in this paper. By ‘twice pre-bending method’ in the first forming step, the springback law can be obtained. With the springback law and the target angle, the exact punch displacement which determines the formed angle in each bending step is predicted. In the succedent forming steps, the bending process is carried out with the exact punch displacement by real-time revising the springback law. And the angle error in each forming step is calculated by comparing the actual formed angle with the target angle. By conducting compensation for the last angle error in the next forming step, each precise bending process step is realized. A system of intelligent control technology for forming the steel pipe was developed. A calibration method is proposed to calculate the exterior parameters of the CCD camera, in which the equilateral triangle is em-ployed as the calibrating board and only one image needs to be captured. A mathematical model, which converts the angle in the image into the actual formed angle, is derived. The experimental results showed that the ellipticity of the formed pipes was less than 1.5% and the high-quality pipes can be manufactured without the worker's operating experience by employing the in-telligent control technology.
文摘In this paper, we have investigated the peristaltic flow of Williamson fluid in a curved channel. The governing equations of Williamson fluid model for curved channel are derived including the effects of curvature. The highly nonlinear partial differential equa- tions are simplified by using the wave frame transformation, long wavelength and low Reynolds number assumptions. The reduced nonlinear partial differential equation is solved analytically with the help of homotopy perturbation method. The physical features of pertinent parameters have been discussed by plotting the graphs of pressure rise, velocity profile and stream functions.
