Multi-island cavities are characterized by complex geometries, irregular boundaries, and discretely distributed islands. Tool paths generated by traditional zigzag cutting often suffer from frequent tool retractions, excessive non-cutting motion, and interference caused by islands. To address these issues, this paper proposes a deep reinforcement learning-based tool path generation method. First, the machining region of a complex cavity is discretized into driving lines, and continuous line groups are constructed through geometric processing and a grouping algorithm. In this way, the tool path generation problem is transformed into a multi-stage sequential decision-making problem, and a Markov Decision Process model is established. On this basis, a Deep Q-Network with prioritized experience replay is employed, enabling the agent to learn the endpoint visiting sequence through interaction with the environment and thereby reduce the total non-cutting motion distance. Compared with the local heuristic method and the classical zigzag scan algorithm, the proposed method reduces the total non-cutting motion distance and the number of tool retractions, especially for complex multi-island cavities. The results indicate that the proposed method has good adaptability and global optimization capability, providing a new solution for tool path generation in zigzag cutting of complex aero-engine cavities.
Aiming at the problems of resonant frequency drift and amplitude instability caused by dynamic load fluctuations during robotic ultrasonic machining, a frequency tracking and amplitude stabilization power supply system based on STM32 was designed and developed in this work. A compound frequency tracking strategy integrating "variable-step maximum current method for coarse tracking and phase difference method for fine locking" was proposed, and amplitude stabilization was achieved through current feedback. In terms of hardware, the system was constructed with a digital control circuit centered on the STM32F103, a power conversion circuit comprising a front-stage Buck voltage regulator and a rear-stage full-bridge inverter, and high-precision feedback sampling circuits. Experimental results indicated that the frequency tracking error of this system was less than 140 Hz under different static loads, the dynamic response time was less than 15 ms, and the amplitude fluctuation could be suppressed within u00B15%. Comparative drilling experiments on Carbon Fiber Reinforced Polymer (CFRP) confirmed that after enabling the amplitude stabilization control, the quality of the hole exit morphology was significantly improved, with a notable reduction in burrs and fiber tear defects, and the cutting force became more stable. This research provides an effective solution for stabilizing ultrasonic energy output in dynamic robotic machining environments and possesses significant engineering application value.
To improve contour accuracy of two-degree-of-freedom parallel mechanisms for complex high-curvature trajectories under strong coupling, nonlinear friction, and nonrepetitive disturbances, a dual-loop contour error control method combining Active Disturbance Rejection Control (ADRC) and task-space-based iterative learning control (TS-ILC) is proposed. In the inner loop, a joint-space velocity-loop ADRC is designed to estimate and compensate lumped uncertainties, including inertial coupling, friction, and external disturbances, thereby enhancing disturbance rejection and weakening inter-joint coupling. In the outer loop, the shortest normal contour error is estimated in task space using the Newton iterative method and mapped into a joint-space learning error through the inverse Jacobian. A PD-type ILC with zero-phase filtering is then applied for repetitive error compensation. A MATLAB/Simulink and Simscape Multibody co-simulation platform is built to evaluate the method under white noise and random step load disturbances. Results on heart-shaped and five-leaf clover trajectories show that the proposed method achieves good robustness and convergence, reducing the maximum contour error by 74.15% and 54.48%, respectively, compared with the method that combines ADRC with joint-space tracking-error ILC. This study provides an effective solution for complex-trajectory contour control of high-speed, high-precision parallel mechanisms.
Heat exchangers, as critical thermal exchange equipment, are widely used in fields such as aerospace and energy chemical engineering. However, the design of traditional heat exchangers is often constrained by structural design and manufacturing processes. The triply periodic minimal surfaces (TPMS), an advanced porous structure derived from nature with mathematically definable properties, offers a novel solution to overcome these limitations when integrated with additive manufacturing (AM). This study employs a parametric design methodology based on TPMS structures to systematically construct a series of heat exchanger models. These models utilize Gyroid, Diamond, and Schwarz as unit cells with varying unit cell dimensions and wall thicknesses. Through thermal-fluid coupling simulations, the effect of key geometric parameters on the macroscopic performance of the heat exchangers is investigated. The results indicate that TPMS structures can effectively enhance heat transfer performance. Smaller unit cell dimensions contribute to intensified heat transfer, with the temperature difference between hot and cold fluids under optimal conditions reduced to 8.74% of the initial temperature difference. Variations in unit cell wall thickness have a minor impact on the performance of the heat exchangers studied here once steady state is achieved. Among the different TPMS configurations, the Diamond unit cell demonstrates superior heat transfer performance due to its multi-branch flow channel structure. This study provides a theoretical foundation and design reference for the development of high-performance heat exchangers based on TPMS structures and additive manufacturing.
Pneumatic systems are important fluid power transmission mechanisms in industrial automation. They use compressed air to transfer energy and signals. However, leaks, which are mainly from seal failures or degrading pipelines, cause many problems. These include unstable pressure, equipment failures, and lower production quality. To offset leaks, air compressors often run harder, wasting energy and raising costs. So, timely and reliable leak detection is crucial for system reliability, cost savings, and safety. This review systematically examines current pneumatic leak detection technologies. First, it covers system basics and common leak points. Then, it evaluates detection methods, from traditional sensors to advanced intelligent algorithms. These are judged on accuracy, speed, and ability to handle environmental interference. The article also discusses challenges in complex environments, the shift toward remote monitoring via multi-sensor fusion, and the Industrial Internet of Things (IIoT). This review provides a foundation for selecting the most effective detection methods and offers key insights for intelligent, energy-saving pneumatic maintenance systems.
To address the mismatch between pressure-bearing capacity and lightweight requirements in additively manufactured liquefied gas micro-propulsion tanks, this paper proposes a morphology-based lightweight design method constrained by mechanical performance. Using R134a (tetrafluoroethane) as the propellant and AlSi10Mg as the manufacturing material, a conformal tank system was designed, with the first-stage and second-stage tanks required to withstand pressures of 2 MPa and 1.6 MPa, respectively. High stress concentration and structural redundancy areas were identified using the von Mises equivalent stress method. Morphology optimization with variable thickness was performed with the objective of minimizing stress. The results indicate that with an optimized rib height of 1.6 mm, the maximum stress is 216 MPa, achieving a 37.07% reduction in mass and an 8.6% increase in propellant capacity. Fatigue and ultimate pressure tests were conducted, demonstrating that the tank's fatigue strength meets the 100-cycle requirement and the stages can withstand 2.1 MPa and 1.6 MPa respectively, satisfying the operational requirements for micro-nano satellites.
Polyimide (PI) light-trapping microstructures have shown great potential in improving the performance of optoelectronic devices. However, its high viscosity characteristic makes it difficult to achieve high-precision and large-area forming by traditional micro-nano fabrication techniques. Especially for the high aspect ratio light-trapping structure, the existing ultraviolet (UV) curing imprinting faces the key challenges of incomplete structure filling and insufficient morphology fidelity. Therefore, the study develops a simulation model incorporating two-phase flow of PI resin during imprint filling, revealing the influence of imprinting time, resin viscosity, and imprinting velocity on the filling completeness of microstructures. The experiments of UV curing imprinting replicated PI micro-pyramid array successfully with 500 u03BCm height and 75u00B0 inclination angle. Through simulation guides optimization of imprinting parameters (imprinting temperature, imprinting force, and imprinting time), the large-area replication of PI micro-pyramid array achieves 96.2% structural height fidelity with inclination angle deviations below u00B1 1u00B0. Optical performance testing indicates that the presence of the light-trapping microstructures reduces the surface reflectance of polyimide in the visible range from 7%-12% to 6%-10%. Furthermore, the reflectance can be lowered below 1% through the deposition of a coating on the surface of these light-trapping microstructures. The research not only overcomes the challenges in the fabrication of high-aspect-ratio PI microstructures but also provides a reliable and efficient method for the mass production of PI-based light-trapping structures. It offers new insights into the application of PI in advanced optoelectronic devices, promoting the development of high-performance and cost-effective photonic components.
Carbon fiber reinforced polymer (CFRP) composites have gained widespread application in aerospace, automotive manufacturing, wind turbine blades, and other fields due to their high specific strength, high specific stiffness, excellent fatigue resistance, and superior corrosion resistance. However, characteristics such as anisotropy and low interlaminar strength render them highly susceptible to various forms of damage during the drilling process, significantly affecting the service performance of the components. This paper presents a systematic review of the formation mechanisms of drilling damage in CFRP, its influence on the mechanical performance of laminates, and recent advances in damage suppression strategies. Typical damage, including fiber burrs, fiber tearing, hole-wall damage, and internal delamination, are first summarized in terms of their characteristics and underlying formation mechanisms, together with the application of acoustic emission techniques for damage identification and monitoring. The effects of drilling damage on the tensile, compressive, flexural, bearing, and fatigue properties of CFRP laminates are then critically discussed, with particular emphasis on the intrinsic correlations between damage evolution and mechanical property degradation. Damage suppression strategies are systematically reviewed from the perspectives of process parameter optimization, dedicated tool development, advanced drilling technologies, and intelligent process control. Followed by a discussion of future research directions, future studies should focus on further elucidating the quantitative relationship between drilling damage and mechanical performance, while advancing multiscale simulation methods, intelligent in-process monitoring, and adaptive control technologies, thereby promoting high-quality and high-efficiency drilling of CFRP components.
Soft robotics represents a paradigm shift in robotics, focuses on creating adaptable, flexible robots inspired by biological systems to engage safely and efficiently with intricate environments and living organisms. This study focus on the investigation of the performance characteristics of 3D-printed Soft Pneumatic Actuators (SPAs) fabricated from thermoplastic polyurethane using Fused Filament Fabrication. Through systematic experimental analysis, we evaluate how geometric parameters and operating conditions affect actuator behavior, specifically examining the relationships between the number of bellows (N), wall thickness (T), and operating pressure (P) on the resulting bending angle (u03B1) and maximum force output (F). Tests were conducted on 45 actuator specimens, with bellows counts of 9, 11, and 13, wall thicknesses of 1.6, 2, and 2.4 mm, and operating pressures ranging from 1 to 3 bar. Results demonstrate approximately linear relationships between design parameters and actuator performance metrics. Increasing the operating pressure showed strong positive linear correlations with bending angle, while wall thickness demonstrated a strong negative linear correlation. For force output, operating pressure maintained a strong positive linear correlation, wall thickness showed a moderate negative linear correlation, while the number of bellows had only a weak positive correlation. Both bending angle and force output exhibited approximately linear relationships with these parameters, with deviations from linearity remaining fairly low across all configurations. The predictable, near-linear responses provide a robust foundation for performance-driven design optimization of SPAs for applications requiring precise control of movement and force generation.
This study investigates linear friction welding of GH4169 alloy for aero-engine integrally blisks, with particular focus on elucidating the mechanisms by which combined pre- and post-weld heat treatments influence microstructural evolution and corrosion behavior of welded joints. Microstructural characterization reveals that composite heat treatment promotes the formation of large-scale spherical u03B3u2032 and disc-shaped u03B3u2032u2032 phases in the Base Material (BM), while in the Thermo-Mechanically Affected Zone (TMAZ), original precipitates coarsen and fine u03B3u2032 and u03B3u2032u2032 phases reprecipitate. Additionally, needle-like u03B4 phases precipitate along grain boundaries. The synergistic effect of grain refinement and precipitation strengthening results in superior joint mechanical properties, including a microhardness of 540 HV0.5, a tensile strength of 1400 MPa, and a fracture elongation of 18%, with the joint strength comparable to that of the BM. Electrochemical analysis shows that the joint exhibits significantly lower corrosion resistance than the BM, due to enhanced micro-galvanic coupling between the u03B3-matrix and precipitated u03B3u2032 or u03B3u2032u2032 phases. This is evidenced by an increase in corrosion current density from 1.62u00D710-6 A/cm2 of BM to 3u00D710-6 A/cm2 of joint. High-temperature molten salt corrosion tests indicate that corrosion mainly occurs through the combined action of oxides and soluble salts. The joint shows accelerated corrosion, reaching a peak value in the average corrosion rate of 269.9 g/m2/h, characterized by a fine-grained microstructure and loosely oxide films. The electrochemical impedance of these is measured at 1.83 ku03A9 u00B7cm2, attributed to thermo-mechanical effects. In contrast, the coarse-grained BM forms dense and protective oxide layers, with a higher impedance of 14.20 ku03A9 u00B7cm2 and a lower peak corrosion rate of 134.9 g/m2, reflecting more stable corrosion behavior. This work deciphers how heat treatment controls corrosion resistance through the regulation of precipitate distribution in welded joints, providing valuable guidelines for the optimization of integrated welding and heat treatment process in blisk production.
In industry 4.0/5.0 era, the demand becomes more uncertain, which requires smarter and more flexible manufacturing systems. Reconfigurable manufacturing systems (RMS) is a typical paradigm for dealing with demand changes supporting by reconfigurable machine tools (RMT). Recently, smart RMS (SRMS) as the evolution version of RMS driven by new technologies (Digital twin, AI, etc.) was proposed. Reconfiguration remains one of the core research topics in RMS/SRMS, yet the lack of empirical reconfiguration data has significantly limited progress. Therefore, this study constructs a new benchmark dataset of RMT reconfiguration times based on desktop-level RMT suites. While this dataset is not a direct representation of industrial-scale RMTs, it provides a valuable initial reference and foundation for subsequent optimization research. And then, a reconfiguration path optimization problem of SRMS with RMTs is investigated based on the proposed benchmark dataset, which the number of RMTs, the reconfiguration time and the cost of reconfiguration and RMT investment are selected as optimization objectives. The NSGA-u2162 algorithm is employed to solve the problem, leveraging its advantage in maintaining solution diversity in high-dimensional objective spaces. Moreover, a case study is provided to implement the proposed benchmark dataset and reconfiguration path optimization method. The results highlight not only the effectiveness of the optimization approach but also the potential and limitations of applying the constructed dataset, paving the way for future validation in industrial-scale SRMS.
This study presents an optimized cold forging process for pinion gears with an inner helical structure, employing Finite Element Method (FEM) simulations and experimental validation. Conventional CNC machining for gear manufacturing often leads to excessive material waste, high energy consumption, and prolonged processing times. To mitigate these challenges, this research utilizes DEFORM-3D simulations to analyze forming load, material flow, and frictional effects during the cold forging process. The proposed method achieves high dimensional accuracy (JIS 6 grade) while reducing forming load and extending tool life through optimized lubrication techniques. The maximum forming load for the pinion gear was determined to be 85 tonf, and the findings indicate that the absence of lubrication increases the forming load by approximately 42.8%, highlighting the critical role of lubrication in cold forging. Furthermore, experimental validation confirmed the reliability of the FEM model, with measured tooth profile errors remaining within the acceptable tolerance range. The results of this study offer valuable insights for the automotive, aerospace, and heavy machinery industries, where high-precision and high-strength gears are essential. The optimized cold forging method enhances manufacturing efficiency, sustainability, and cost-effectiveness by minimizing material waste, reducing tool wear, and improving the feasibility of mass production.
Aiming at the demand of variable configuration and reconfigurable antenna technology for space equipment such as satellites, a frequency reconfigurable antenna manufacturing method based on laser Selective Melting (SLM) NiTi shape memory alloy is proposed. Firstly, the SLM process is studied by experiments, and the electromagnetic properties of NiTi alloy with defects are analyzed. The shape memory effect and the functional characteristics of superelasticity are revealed. On this basis, a frequency reconfigurable satellite antenna based on NiTi shape memory alloy is developed. S11 measurement and microwave darkroom gain test show that the antenna is tunable in the 7.7-12.6 GHz band, with a maximum gain of 6.2 dBi and a reflection loss of less than u221210 dB.
Planar double-enveloping hourglass worm drive has attracted much attention due to its high performance. It is widely used in modern industrial fields and conforms to the development trend of gear technology. This paper deeply discusses its design and machining. In terms of design technology, the mathematical model construction is summarized, and it is pointed out that the meshing performance can be significantly improved by optimizing the worm parameters and tooth surface modification. At the level of machining technology, advanced processes such as CNC turning, virtual rotary center technology, five-axis linkage machining, rotary cutting and four-axis machining are comparative analysis. It is emphasized that these technologies play an important role in improving machining efficiency and accuracy and reducing costs, and it is pointed out that there is still room for further improvement. Finally, this paper looks forward to the design and machining of the planar double-enveloping hourglass worm, and puts forward suggestions for future research directions.
This study systematically explores the friction and wear reduction mechanism under the synergistic effect of composite coating and composite micro-texture on ductile cast iron. The preparation process of the composite coating is optimized by using polytetrafluoroethylene (PTFE) as the base material and nano-alumina as the reinforcing agent. The composite micro-texture is efficiently fabricated by using a picosecond laser. Dry friction experiments show that the coating effectively improves the anti-friction performance of the ductile cast iron surface, and the added nano-alumina significantly enhances the wear resistance of the coating. The laser processing increases the hardness of the ductile cast iron surface, and the fabricated micro-texture can effectively store the coating and capture wear particles, the fabricated micro-texture can also slowly release the coating during subsequent friction processes, ensuring a low coefficient of friction (COF) and wear over a long friction time. Compared with the original samples, the average COF and wear mass of ductile cast iron with composite coating and composite micro-texture are decreased by 77% and 93.8%, respectively.
Aluminum alloy stamped parts are widely used in highprecision industrial fields such as aerospace and automotive industries, where timely crack detection is crucial to ensure their performance and safety. Traditional crack detection methods mainly rely on manually designed feature extraction algorithms. While certain success has been achieved in simple scenarios, there are still limitations in detection accuracy and robustness when dealing with complex backgrounds and significant variations in crack morphology. This paper proposes a crack detection method called CGCYOLO, which integrates Channel Aware Fusion (CAF), GSSPPF, and Cross Scale Path Aggregation Network (CSPAN) to enhance the modelu2019s feature extraction and detection capabilities. Experimental results show that CGCYOLO demonstrates higher accuracy and stronger robustness in crack detection tasks for aluminum alloy stamped parts, indicating its broad application potential.
In this paper, the research on control of intermetallic compound during aluminum/steel friction stir lap welding is reviewed. Several means that improve the properties and quality of the joints are presented by controlling the IMCs layer. The thickness of IMCs layer is controlled by the processing parameters, tool structure and aided processing, and the types of the IMCs are controlled by the processing parameters and the addition of the interlayer design. Advantages and disadvantages of the above methods are discussed. A new research direction with a large-lift angle structure of the tool is also proposed for the development of the aluminum/steel welding technology in this paper.
To establish the mechanism of millisecond laser processing of SiCf/SiC ceramic matrix composites, and to support the design and optimization of millisecond laser processing techniques, this paper conducted experimental and simulation studies. The research focused on the ablation threshold of millisecond laser processing of SiCf/SiC ceramic matrix composites and laser scribing experiments, investigating the removal mechanism of these materials. By measuring scribing width, depth, and thermally affected zone thickness, the study revealed the removal mechanism of millisecond laser processing of SiCf/SiC ceramic matrix composites and the influence of different laser process parameters on processing outcomes. The results indicate that effective ablation processing of SiCf/SiC ceramic matrix composites can be achieved at a laser processing speed of 1 mm/s; the ablation threshold for SiCf/SiC ceramic matrix composites is approximately u03A6th = 0.013 J/cm2. The increasing laser energy density results in higher processing depth, width, and thermal affected zone thickness, with depth showing the most significant increase, approximately 1870.07 u03BCm. Increasing the equivalent pulse number enhances processing depth and width, but reduces the thermal affected zone thickness by approximately 6.0 u03BCm.
