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- 저자 : Congbo Li (검색결과 2 건)
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Energy Dissipation Characteristics Modelling for Hot Extrusion Forming of Aluminum-Alloy Components
Hongcheng Li,Yuanjie Wu,Huajun Cao,Feng Lu,Congbo Li 한국정밀공학회 2022 International Journal of Precision Engineering and Vol.9 No.6
The hot extrusion forming process is widely used to process aluminum-alloy components in both the automobile and aircraft manufacturing industries. Since it involves pushing the material through the die at increased temperature, it is very energy-intensive despite requiring less blank material allowance. During hot extrusion forming, the multi-stage dynamic conversion of electricity, mechanical energy, and hydraulic energy to heat results in high energy dissipation. In order to improve the power and energy conversion efficiency of hot extrusion forming process, it is necessary to identify the energy dissipation characteristics. The transfer and conversion paths of the electrical, mechanical, and hydraulic energy from the motor to the hydraulic cylinder were firstly depicted based on the motion cycle of the extruder. A bond graph-based energy dissipation model was then proposed for dynamically identifying the energy-saving potentials. The energy dissipation model integrated the power bond graph sub-model of energy conversion elements such as motor, pump, hydraulic valve group, and hydraulic cylinder. These power bond graph sub-models were separately developed to find the energy dissipation state equations of energy conversion elements. An experiment was carried out using data obtained from the energy management system to validate the bond graph-based energy dissipation model. The results have shown that the power and energy conversion efficiency of hot extrusion forming is primarily controlled by the parameters such as extrusion velocity and extrusion force. Both the higher extrusion velocity and lower extrusion force will reduce the power and energy conversion efficiency. An optimal combination of extrusion velocity and pressure can achieve the lowest energy consumption per unit product.
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Xikun Zhao,Congbo Li,Xingzheng Chen,Jiabin Cui,Bao Cao 한국정밀공학회 2022 International Journal of Precision Engineering and Vol.9 No.3
Cutting parameters and machining configurations affect the energy consumption and production time in the machining process significantly. Previous cutting parameters optimization methods are proposed for a specific machining configuration that limits its generalization ability. However, the machining configuration varies constantly with actual machining tasks, which results in the predetermined optimization method is impractical. We propose a data-driven optimization method for the multiple machining configurations, aimed at reducing energy consumption and production time. Firstly, the analysis of the relationship between energy consumption and meta-actions under different machining states is carried out, and the Gaussian process regression (GPR)-based energy consumption model is proposed. Then, a multi-objective optimization model is proposed for energy consumption and production time reduction, which is solved via a multi-objective grey wolf optimization. Finally, the experiments are conducted to verify the validity of the proposed method and the influence of metaactions on energy consumption and production time are explicitly analyzed. The case study indicates the proposed energy consumption model has better prediction accuracy for multiple machining configurations. Optimizing cutting parameters achieves a trade-off between energy consumption and production time. Moreover, the parametric influence indicates cutting speed is the most influential cutting parameter for energy consumption and production time.
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