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Dong Kai,Rong Qianqian,Xiao Ruirui,Gao Yunfei,Wang Fuchen 한국화학공학회 2024 Korean Journal of Chemical Engineering Vol.41 No.4
Liquefi ed natural gas production plants usually suff er from line blockage, which causes economic, environmental, and safety issues. The blockage, mainly caused by the solidifi cation of heavy hydrocarbons, should be avoided or mitigated by removing the impurities as thoroughly as possible. In this work, we proposed a scheme taking cryogenic liquefi ed propane as absorbent to absorb heavy hydrocarbons in the liquefi ed natural gas production process. This paper fi rst investigated freeze-out profi les of liquefi ed natural gas combined with marginal benzene and toluene by the ThermoFAST simulator, which showed that the precipitated solid tended to form under a low temperature, which posed challenges in purifi cation. Subsequently, the feasibility of using liquefi ed propane as an absorbent to remove benzene and toluene was studied using Aspen Plus. A cryogenic absorption and regeneration process for liquefi ed natural gas purifi cation was proposed, and factors infl uencing the performance were investigated. The results showed that the hydrocarbon impurities are removed more thoroughly at a high fl owrate of the recycled absorbent stream. The absorption process exhibited an apparent cooling eff ect mainly caused by the vaporization of liquefi ed propane to the gas phase, and the higher operation temperature impedes the vaporization process. For a better purifi cation eff ect, the system should be operated under a lower pressure or with a higher recycled absorption solution fl owrate. Based on the design simulation results, utilizing liquefi ed propane as an absorbent to remove heavy hydrocarbons is novel and promising for LNG purifi cation.
Visual Attention Servo Control for Task-specific Robotic Applications
Dong Liu,Ming Cong,Yu Du,Yunfei Zhang,Clarence W. de Silva 제어·로봇·시스템학회 2013 International Journal of Control, Automation, and Vol.11 No.6
This paper proposes a visual attention servo control (VASC) method which uses the Gaussian mixture model (GMM) for task-specific applications of mobile robots. In particular, low dimensional bias feature template is obtained using GMM to get an efficient attention process. An image-based visual servo (IBVS) controller is used to search for a desired object in a scene through an attention system which forms a task-specific state representation of the environment. First, task definition and object representation in semantic memory (SM) are proposed, and bias feature template is obtained using GMM deduction for features from high dimension to low dimension. Second, the features intensity, color, size and orientation are extracted to build the feature set. Mean shift method is used to segment the visual scene into discrete proto-objects. Given a task-specific object, top-down bias attention is evaluated to generate the saliency map by combining with the bottom-up saliency-based attention. Third, a visual attention servo controller is developed to integrate the IBVS controller and the attention system for robotic cognitive control. A rule-based arbitrator is proposed to switch between the episodic memory (EM)-based controller and the IBVS controller depending on whether the robot obtains the desired attention point on the image. Finally, the proposed method is evaluated on task-specific object detection under different conditions and visual attention servo tasks. The obtained results validate the applicability and usefulness of the developed method for robotics.
Yanbin Luo,Yunfei Wu,Jianxun Chen,Fangfang Dong,Weiwei Liu,Lijun Chen,Yao Li,Zhou Shi 대한토목학회 2022 KSCE JOURNAL OF CIVIL ENGINEERING Vol.26 No.1
Rock mass pressure has always been a research hotspot in the field of tunnel engineering, especially in the super large-span tunnel, which is characterized by flat section, large excavation span, and complex stress field. Based on the Letuan Tunnel (a bi-directional tunnel with eight traffic lanes) of Binlai expressway expansion project in Shandong Province, China, this paper focused on the calculation method of rock mass pressure and the evolution law of load release in the construction process of the super large-span tunnel excavated by upper-bench central diaphragm (CD) method. Based on field measured data of Letuan Tunnel, the deformation behavior of primary lining and the distribution state of rock mass pressure during the tunnel construction were analyzed. According to the bearing mode of supporting structure, the mechanical models of different construction stages were established. Then, the rock mass pressures in different construction stages were back-calculated using mechanical models and compared with the measured values, and the evolution law of load release during the tunnel construction was discussed. The study results show that the tunnel deformation and rock mass pressure were significantly affected by the construction process and support form, and the excavation span was the key factor affecting the stability of rock mass. For the shallow-buried super large-span tunnel constructed by upper-bench CD method, the primary support of upper bench was under eccentric pressure. The comparison between the back-calculated value and the field measured value indicated that they were similar, and the average relative error was 17.23%. According to the concept of load release coefficient proposed in this paper, the load release coefficient after the pilot tunnel ahead (Part I) excavation reached 63%, and the load release coefficient after the pilot tunnel behind excavation (Part II) was 37%, which means that the rock mass pressure of Part I is increased about 59% due to the excavation of Part II.
The Method of Aiming towards the Normal Direction for Robotic Drilling
Yuhao Gao,Dan Wu,Yunfei Dong,Xinguo Ma,Ken Chen 한국정밀공학회 2017 International Journal of Precision Engineering and Vol.18 No.6
During the robotic drilling of an aircraft assembly, the normal directions of the workpieces are to be measured to guide the robot by aiming the spindle at the real normal directions of the curved surfaces. This paper describes the development of a method of using four laser displacement sensors to measure the normal direction and the implementation of the proposed method in a robotic drilling system to meet industrial application requirements. First, a novel mechanical structure is introduced to achieve a higher installation accuracy for the laser displacement sensors with a micro adjusting method. Next, the hardware structures and a convenient method of calibrating the sensors are introduced. To accommodate the complexity of the industrial circumstance, a procedure of measuring and adjusting is developed with consideration of both an angular deviation threshold and a limited adjusting iteration. Finally, the experiments of measuring and adjusting iteratively show that two iterations can achieve a satisfactory angular deviation of 0.1° for planar workpieces and three iterations are required for curved workpieces, with the perpendicularity errors of the drilled holes being less than 0.3°. The results can meet the required perpendicularity accuracy of 0.5°.