Cutter design and multi-objective optimization of machine for cable peeling is proposed to use mechanical peeling instead of manual peeling in this paper. First, the design of the machine for cable peeling includes executive mechanism, driving part for cable, driving part for executive mechanism, and peeling mechanism. Then, the cutting experiment platform is set up to verify the actual effect of cutting, and different cutting depths, cutting speeds and fixing cables methods are discussed by the cutting experiment platform. A numerical simulation method is proposed, and different cutting methods, cutting depths and cutting speeds for cutting different materials are discussed by simulation method. The results show that simultaneous cutting is better than sequential cutting. The results show a good agreement between the results obtained from the finite element modelling and experimental investigations. A theoretical reference is provided for subsequent structural improvement. Finally, multi-objective optimization of machine for cable peeling is realized. The aim of the optimization was improving the dimensional accuracy after cutting and reducing the deformation of the cut surface. Cutter thickness, cutter angle, and cutter material are used as optimization variables, and the final optimal solution is obtained. The cutter is manufactured according to the final optimal solution, experiment of cutting is performed, and good agreements were achieved between optimal solution and experiments. Comparing the final results with the initial results shows a significant improvement.
This study is mainly about the optimization, simulation and experiment of a Counter-rotation Straw Returning Cultivator (CSRC), aiming at the problems that the existing CSRC has serious entanglement of grass, terrible jam of soil, large energy consumption, and poor straw coverage rate. Besides, an optimized Rotary Blade Roller (RBR) and a device to avoid the jam of soil were designed to optimize CSRC. A discrete element simulation model of straw-soil-RBR was established based on the EDEM software. The optimization simulation experiment of 4 factors and 3 levels, which took the single-blade operation width, bending angle, advance speed and rotation speed of RBR as factors, and used the straw coverage rate and power consumption as evaluation indicators, was carried out to optimize the structure parameters and working parameters of the RBR with the method of orthogonal experiment. The simulation experiment results showed that the optimal combination of parameters of the RBR at the tillage depth of 130 mm were 237.58 r/min of RBR rotation speed, 1.11m/s of forward speed, 35 mm of single-blade working width, and 134.09° of bending angle. Field tests showed that the straw coverage rate was 89.29%, the average torque was 517.25 N·m, the soil fragmentation rate was 83.21%, and the flatness of the surface after cultivation was less than 4 cm under the conditions of optimal parameters mentioned above. Therefore, the CSRC perfectly satisfied the industry standards, and meet the design requirements of machinery.
The present paper describes a method for determining geometries of gear-honing wheels used in the final process for manufacturing automotive transmission gears. Inappropriate geometries of gear-honing wheels could cause large undulations on finished gear-tooth flanks, and the finished gear would be out of the required accuracy. In such cases, the geometries of gear-honing wheels are required to be modified iteratively until the finished gears have sufficient accuracy. The change in meshing stiffness of a gear-honing wheel and a finished gear significantly affects the rotational synchronization. The poor rotation synchronization could cause the large undulation on a finished gear-tooth flank, to be different from the target micro geometries. This paper presented a geometrical approach that was proposed for a determination method of gear-honing-wheel geometries. The method allows the meshing stiffness to be balanced. Gear-honing wheels designed with the proposed method induced the desired micro geometries of finished gear-tooth flanks in gear-honing experiments. Therefore, the proposed method with the geometrical approach could be useful for the determination of gear-honing-wheel geometries.
This research aims to provide a novel nanofluid / minimal lubrication (MQL) technology for 7075-T6 aluminum alloy microdeep drilling. This technology will extend the life of tools used for precision machining. A parameter combination meeting the optimal quality-related objectives was obtained, and a predictive model was developed. Because microdrilling force and torque were two quality-related objectives, this study adopted Taguchi’s robust design, used machining parameters (i.e., nanofluid weight percentage concentration, spindle speed, feed rate, nozzle distance, nozzle angle, MQL flow, air compression, and pecking depth), and performed grey relational analyses to obtain the parameter combination generating the optimal microdrilling force and torque. Subsequently, this study used a neural network and conducted Taguchi grey relational analyses (where Taguchi orthogonal tables were used as the experimental basis and the experimental data from grey relational analyses were used as training examples) to develop a highly accurate microdrilling predictive model. The parameter combination for generating the optimal microdrilling force and torque predicted differed from those of the experiment results by only 0.44% and 1.24%.
There are lots of general parts with frequent maintenance and high interchangeability for continuous casting machine during its operation and maintenance. To acquire the service information of each general part under the environment of high temperature and serious oil pollution for predicting remaining life and preventative maintenance, a digital twin-driven monitoring and traceability system for general parts in continuous casting machine is proposed. First, the systematic architecture of proposed approach is given in detail, where a typical five-layer model for digital twin-driven monitoring and traceability is established. Second, the Web-based 3D visualization monitoring for continuous casting machine is achieved by using lightweight 3D twin model. After that, an assembly model based on polychromatic sets is built for expressing and describing the assembly relationships and assembly process of general parts. Meanwhile, an encoding rule for part and position is put forward by considering assembly position information. On the basis of that, the general parts with total process information are traced in the service life cycle. Finally, digital twin-based 3D visualization monitoring and traceability prototype system is developed and implemented, where the experiment cases verify the effectiveness and feasibility of the proposed approach.