The complexity of aeroengine external piping systems necessitates the implementation of automated design processes to reduce the duration of the design cycle. However, existing routing algorithms often fail to meet designer requirements because of the limitations in providing a single solution and the inadequate consideration for route constraints. In this study, we propose the multi-solution pipe-routing method for aeroengines. This method utilizes a hybrid encoding approach by incorporating fixed-length encoding to represent route constraints and variable-length encoding and indicate free-exploration points. This approach enables designers to specify route constraints and iterate over the appropriate number of control points by employing a modified genetic iteration mechanism for variable-length encoding. Furthermore, we employ a pipe-shaped clustering niche method to enhance result diversity. The practicability of the newly proposed method is confirmed through comparative experiments and simulations based on the “AeroPiping” system developed on Siemens NX. Typical solutions demonstrate significant differences in circumferential and axial orientations while still satisfying engineering constraints.
End worm gear drives are characterized by their multi-tooth contact, compact contour, and theoretical potential to overcome some inherent flaws of cylindrical worm drives. However, quantitative basic research on end worm gear drives is currently inadequate, which hinders the development of this transmission. This work focuses on the computational design of end worm gear drives and proposes a new Niemann-type design. Meshing models of the proposed drive are established, and its engagement theory is deduced systematically. Based on the derived tooth surface equations, an innovative research methodology for the tooth curve geometry of the end worm gear is created, and the tooth curve in the worm gear reference plane is proved to be a spiral. An improved formula for the lubrication angle is developed, which can provide more rational numerical results for the angle. Theoretically, the modified formula is universally applicable for line contact drives and can be used to quantitatively investigate the lubrication level between the teeth for the proposed drive. Simulation outcomes demonstrate the favorable characteristics of the transmission, including broad conjugate areas, even contact lines, and fine global lubrication state.
In ocean exploration, underwater hydraulic manipulators (UHMs) driven by water hydraulics may become favored over oil-based systems because of their eco-friendliness and ability for continuous operation. A water hydraulic high-speed on/off valve (WHSV), with good sealing and fast response, may be used as a core control component of UHM. The comprehensive performance of the WHSV needs to be improved to enhance the accuracy, continuity, and reliability of UHM. In this study, the relationship between the negative voltage and the WHSV characteristics, including dynamic performance, power losses, and impact performance, is studied by finite element simulation. Furthermore, a multi-objective optimization method is proposed to improve the comprehensive performance of the WHSV. This method integrates the optimal Latin hypercube sampling method, universal Kriging surrogate model, non-dominated sorting genetic algorithm II, and Technique for Order Preference by Similarity to Ideal Solution methods to optimize the equivalent amplitude and duration of the negative voltage. Our findings reveal that the closing time decreases with the increase in the equivalent amplitude and duration of the negative voltage, while the opposite is observed in the power losses and maximum impact equivalent stress of the valve seat. Optimization results show a slight 3.3% increase in closing time of the WHSV but significant reductions in total power loss (9.8%), maximum impact equivalent stress (14.5%), and maximum total deformation (19.8%). This study provides a practical optimization approach for enhancing the comprehensive performance of the WHSV for improved UHM operation.
Multiple process variable parameters such as cutting parameters, tool parameters, and machine tool parameters in gear hobbing and subsequent gear grinding processes directly affect gear machining accuracy and efficiency, as confirmed through historical processing experience or manual decision-making. To determine effective parameters quickly, this study proposes a new biomimetic approach for optimization and decision-making based on the improved multi-objective grasshopper optimization algorithm (MOGOA) and the information entropy technique for order preference by similarity to ideal solution (information entropy-TOPSIS) for gear hobbing and gear grinding collaborative machining. Specifically, the parameter optimization problem under collaborative machining of gear hobbing and gear grinding is presented. Then, a multi-objective model oriented to the optimization of gear accuracy and processing efficiency is constructed through optimization variables, i.e., hobbing and grinding process parameters. Furthermore, the improved MOGOA and information entropy-TOPSIS are used for optimal decision-making on the process parameter sets. Eventually, the effectiveness and practicality of the proposed multi-objective optimization decision-making method are verified via small module gear precision machining. Results and comparison demonstrate that the optimization and decision of multiple parameters for the collaborative machining of gear hobbing and gear grinding can be solved by the proposed method, whose efficiency and superiority are confirmed.
This study proposes a data-driven friction modeling and compensation method aimed at solving the problem of servo performance degradation caused by friction in rotary servo actuators. First, a data-driven friction modeling method is proposed on the basis of the physics-informed neural network (PINN) and the LuGre model. The constructed friction model consists of sliding regime, static regime, and presliding regime, which extends the variables of the friction model to include velocity and position. The data-driven friction model not only retains the accuracy of the LuGre model in describing the dynamic behavior of friction at zero velocity but also improves the accuracy and convergence speed of the model through the powerful learning ability of PINN, which is verified in the two examples of constructing friction test data. Second, on the basis of the data-driven friction model, a composite compensation strategy centered on friction compensation is proposed. The friction compensator is used to compensate the internal friction of the actuator, and the extended Kalman filter is used to suppress the random disturbance to achieve the precise control of the servo actuator. Experimental validation of the proposed compensation strategy against three traditional control methods demonstrates its superiority, with average improvements of 49.5%, 30.4%, and 32.7% in velocity tracking accuracy, respectively, while ensuring consistent accuracy across different positions. The proposed data-driven friction modeling and compensation method provides a new perspective and method for overcoming the effect of friction.
Hybrid deposition with microrolling is a promising arc-based direct energy deposition technique to rapidly build complex parts, whose performance is comparable to that of their wrought counterparts. Complex forming conditions and bead morphologies pose difficulties in controlling the morphologies from a single weld bead to built part profiles, and these difficulties hinder the widespread application of the technique. Here, a model that can automatically generate optimal process parameters on the basis of the infrared image, including thermal information and the point cloud information of the target weld bead, is developed. Results show that the errors in critical parameters, namely, feed speed, travel speed, and rolling force, are below 0.4%, 0.9%, and 2%, respectively, indicating that the proposed technique outperforms the compared methods. Furthermore, validation reveals that the actual depositing bead is similar (deviation below 0.05 mm) to the target bead. The proposed strategy provides an effective foundation for dynamic path planning and can considerably improve printing efficiency and precision.
Laser directed energy deposition (LDED) is widely used in the remanufacturing and surface strengthening of high-value thin-walled components. However, the transformation mechanism of mechanical properties for substrates induced by laser deposition, especially for thin metal sheets, remains unclear. In this study, the affecting mechanism of Fe304 coatings fabricated by LDED on the ductility of Q235 thin plates was investigated. Samples of original substrate (OS), deposited plates with one to three layers of coating (D1–D3), the substrate zone of deposited plates with one to three layers of coating (D1-S–D3-S), and deposited coating were prepared to evaluate the effect of coating and laser heat on substrate ductility. The Fe304 coating deposited by LDED and the accompanying laser heat drastically reduced substrate ductility by about 87%. Specifically, laser heat reduced the ductility by 24%–51%. The Fe304 coating deposited by LDED led to the ductile-to-brittle transition of the substrate. Compared with ductile dimples in the OS, cleavage fracture was found in the substrate of deposited plates. Meanwhile, the mechanisms of ductile-to-brittle transition of the substrate were analyzed. Laser heat caused the precipitation of cementite and the generation of a decarburization layer in the substrate. Coating resulted in the pileup of dislocations in the substrate, then nonuniform deformation occurred in the substrate. The cracks of the coating fracture extended to the substrate, inducing local cracking of the substrate. This study provides fundamental guidance for the surface manufacturing of ductile thin-walled components through LDED.
Laser cleaning technology has emerged as a rapidly developing high-tech surface engineering technology in recent years. It is considered the most promising green cleaning technology in the 21st century, and related patent applications exhibit an explosive growth trend. This study summarizes the overall trend of patent applications in laser cleaning in China, with a focus on systematically analyzing patents related to cleaning different substrates and coatings, cleaning equipment, and processes over the past 6 years. The main characteristics of the growth trend, institutional attributes, regional distribution, and type proportion of laser cleaning patent applications in China are clarified. The patent application characteristics of laser cleaning for different substrate materials and coatings are identified. The progress in research and development of laser cleaning equipment, cleaning terminals, and monitoring devices is outlined, while potential for maintaining substrate surface integrity and achieving surface functionalization through laser cleaning is explored. Areas for improvement in laser cleaning are determined to support the innovative development of laser cleaning technology.
This study proposes an adaptive control strategy for unmanned mining shovel digging trajectory tracking based on radial basis function neural network (RBFNN) and a class of unmanned mining shovel time-varying systems with model uncertainty and external disturbances. A new set of Lagrangian dynamics differential equations is reconstructed by utilizing the kinematic model of the electric shovel and considering external disturbances along with modeling uncertainties. This approach lays the groundwork for subsequent adaptive controllers. The proposed controller is designed to regulate the position errors of the unmanned mining electric shovel system, which is characterized by a complex structure, high load, large size, and strong coupling. It takes the deviation values and their derivatives of the lifting and pushing movements as inputs and adjusts the output torque to converge the bucket position to the desired trajectory. The controller utilizes the RBFNN in the control law to compensate for uncertainties in this type of system with large disturbances and inertia. This compensation helps eliminate the impact of external disturbances and modeling uncertainties on the unmanned mining electric shovel’s ability to follow the excavation trajectory. The consistent boundedness of the closed-loop system’s ultimate limits is proven through Lyapunov stability theory. Finally, the effectiveness of the proposed solution is validated through simulation experiments.
