Search Results (338)

The main dimensional errors in stamped parts are caused by the springback phenomenon. Those errors usually lead to assembly difficulties and/or the malfunction of those parts. The objective of this contribution is to give a comprehensive and detailed view of the sheet metal-forming process of an actual industrial part, with the focus on the setup adjustment of the blank-holder force (BHF), using the springback as the determining factor of the manufacturing quality. The complete cycle of the simulation will be detailed from the experimental determination of the model parameters to the correlation with experimental results of the simulated values. Many studies use simple geometries with limited practical application, failing to provide a quantitative understanding of actual springback in industrial processes. This work aims to offer a realistic reference for springback in a real production part, combining numerical prediction during design using a well-established model and experimental measurements in the factory. The simulation, carried out using LS-DYNA, determines the influence of the BHF in the springback observed in the manufacturing process of a gas cooktop part made from non-stable austenitic 1.4301 steel. The material has been modeled using Barlat’s Yld2000, experimentally determining the strain rate-dependent hardening, yield locus and isotropic–kinematic hardening. To validate the model, an experimental campaign has been developed, testing the part with values of BHF within the range of 50 t to 200 t. The results show that the numerical model is able to represent the influence of the BHF on the springback, demonstrating the relation between them. Full article

The working accuracy of space optical payloads, sensitive components, greatly depends on the pointing accuracy and stability of the platform. This article establishes a mathematical model for relative position and attitude measurement based on PSD and eddy current and analyzes the failure modes under the measurement models. Through model derivation, it can be concluded that the position and attitude measurement system has high redundancy; in the event of sensor failure in the horizontal or vertical direction, relative position and attitude measurement and resolution can still be completed, which solves the relative measurement problem of position and attitude measurement of the space Maglev vibration isolation control system, providing high-precision closed-loop control for the control system to achieve high-precision pointing and stability. In response to the requirements of high-precision non-contact displacement and attitude measurement, eddy current sensors were selected, and a sensor circuit box was designed. The testing and calibration system adopts an eight-bar Maglev layout, and the actuator has unidirectional dual-mode output. The actuator adopts a double closed magnetic circuit structure, and the coil adopts a winding single-coil structure. The system includes a multi-degree-of-freedom high-precision coil spatial pose automatic positioning platform, a strong magnetic structure, strong uniform magnetic field magnetization, an integrated assembly testing platform, etc. According to the test data, the driver has strong linearity in both low- and high-current ranges. The relative output error in the low-current range does not exceed 0.1 mA, and the relative output error in the high-current range does not exceed 2 mA. After fitting and calibration, it can meet the design requirements. Within redundant designing, fault mode analyzing, and system testing, the relative measurement system can ensure the working accuracy of the optical payload of the spacecraft, which reaches the advanced level in the field. Full article

This study investigates the progressive compressive behavior of modular interior frames with rotary-type module-to-module inter-modular (M2M) connections under sequential column failure. A novel two-stage testing protocol was applied, compressing the left upper column to failure, followed by the right, to simulate realistic loading progression in prefabricated column-supported volumetric modular steel structures. Detailed refined finite-element models (FEMs) were developed and validated against experimental results, accurately capturing local and global responses with an average prediction error of 2–10% for strength and stiffness. An extensive parametric study involving varying frame configurations evaluated the influence of frame member geometric properties, connection details, and column/beam gap interaction on progressive collapse behavior. The results demonstrated that upper columns govern failure through elastic–plastic buckling near M2M joints while other members/connections remain elastic/unyielded. Increasing column cross section and thickness significantly enhanced strength and stiffness, while longer columns and prior damage reduced capacity, particularly during right-column loading. Conventional steel design codes overestimated column strength, with mean P_u,FEM/P_u,code ratios below unity and high scatter (Coefficient of variation ~0.25–0.27), highlighting the inadequacy of isolated member-based design equations for modular assemblies. The findings emphasize the need for frame-based stability approaches that account for M2M joint semi-rigidity, sway sensitivity, and sequential failure effects to ensure the reliable design of modular steel frames under progressive compressive loads. Full article

Aiming at the efficiency bottleneck and error risk caused by the over-reliance on manual experience in traditional assembly sequence planning, the urgent demand for deep reuse of multi-source knowledge in complex products, and the growing demand for resource saving and sustainable development, this study focuses on the core problem of the lack of empirical knowledge modeling and reasoning mechanism in the assembly process of complex products, and proposes a three-phase assembly sequence intelligent planning method that integrates deep learning and ontology theory. Method: First, we propose an instance segmentation model based on the improved Mask R-CNN architecture, incorporate the ResNet50 pre-training strategy to enhance the generalization ability of the model, reconstruct the Mask branch, and add the attention mechanism to achieve high-precision recognition and extraction of geometric features of the assembly parts. Secondly, a multi-level assembly ontology semantic model is constructed based on the ontology theory, which realizes the structured expression of knowledge from three dimensions: product structure level (product–assembly–part), physical attributes (weight/precision/dimension), and assembly process (number of fits/direction of assembly), and builds a reasoning system with six assembly rules in combination with the SWRL language, which covers the core elements of geometric constraints, process priority, and so on. Finally, experiments are carried out with the example gearbox as the validation object, and the results show that the assembly sequence generated by the method meets the requirements of the process specification, which verifies the validity of the technology path. By constructing a closed-loop technology path of “visual perception–knowledge reasoning–sequence generation”, this study effectively overcomes the subjective bias of manual planning, integrates multi-source knowledge to improve the reuse rate of knowledge, and provides a solution of both theoretical value and engineering feasibility for the intelligent assembly of complex electromechanical products, which reduces the R&D cost and contributes to the sustainable development. Full article

In this paper, an accurate error compensation method based on geometric parameter correction and process optimization is proposed for the problem of coupling error in a heavy-load longitudinal and transversal swing table (HLTST) under space constraints, which makes it difficult to control the position efficiently and accurately. The key geometric parameters of pitch and roll layers are determined according to the machining process and assembly relationship, and the kinematic model is modified to effectively reduce the impact of contour error on the system’s accuracy. A coupling error model is established and its transmission mechanism is analyzed to develop a positioning error compensation strategy. Numerical simulation is employed to examine the distribution law, sensitivity, and volatility of independent error and coupling error. This aids in optimizing the design of the table’s machining process by balancing machining accuracy and economy. After the identification of the error parameters, the error compensation model is verified using the uniform design experimentation. The experimental results demonstrate 96.94% and 65.63% reductions in absolute average errors for the pitch and roll angles, respectively, especially when the maximum positioning error under the maximum load condition is controlled within ±5%, which significantly enhances motion accuracy and robustness under complex working conditions. This provides theoretical support and practical guidance for real-world engineering applications. Full article

Internal helical gear pairs are sensitive to manufacturing and assembly errors, loading deformation, which can result in vibration and noise. Three-dimensional topological modification of tooth surfaces is available to reduce this sensitivity. A 3D topological modification method is proposed by means of an internal helical gear form grinding method. The modified tooth surface model was constructed using spatial meshing theory and matrix transformations. Loaded tooth contact analysis (LTCA) was established to investigate the effect law of modification parameters on gear loading performance. Simulation results indicated that the contact area appeared at the middle area of the tooth surface under design loading conditions, with little edge contact existing. Transmission error decreased by up to 28.4% compared to the tooth without modification. The dynamic meshing performance of the internal helical gear pair was enhanced significantly. A transmission experiment was conducted to verify the effectiveness and validity of the simulation results. Full article

In laser-directed energy deposition (LDED) additive manufacturing, stress-induced deformation and cracking often occur unexpectedly, and, once initiated, they are difficult to remedy. To address this issue, we previously proposed the Dynamic Counter Method (DCM), which monitors internal stress based on deposition layer shrinkage, enabling real-time stress monitoring without damaging the component. To validate this method, we used AlSi10Mg material, which has a low melting point and high reflectivity, and developed a high-precision segmentation network based on DeeplabV3+ to test its ability to measure shrinkage in high-exposure images. Using a real-time reconstruction model, stress calculations were performed with DCM and thermal–mechanical coupling simulations, and the results were validated through XRD residual stress testing to confirm DCM’s accuracy in calculating internal stress in aluminum alloys. The results show that the DeeplabV3+ segmentation network accurately extracted deposition-layer contours and shrinkage information. Furthermore, DCM and thermal–mechanical coupling simulations showed good consistency in residual stress distribution, with all results falling within the experimental error range. In terms of stress evolution trends, DCM was also effective in predicting stress variations. Based on these findings, two loading strategies were proposed, and, for the first time, DCM’s application in online stress monitoring of large LDED components was validated, offering potential solutions for stress monitoring in large-scale assemblies. Full article

Surface roughness plays a crucial role in determining surface quality, influencing factors such as vibration, noise, assembly precision, lubrication, and wear resistance in bearings. This research examines how surface roughness (Sa) affects the friction and wear characteristics of GCr15 steel under conditions with adequate oil lubrication while varying the applied load. The findings indicate that with an increase in Sa, the friction coefficient of GCr15 steel also increases. As the load rises from 15 N to 35 N, the friction coefficient remains relatively constant. However, higher loads lead to more severe wear of the microprotrusions on the surface of GCr15 steel. The wear area first decreases and then increases as Sa increases. The minimum wear area occurs when Sa is 0.5 μm. Additionally, a back propagation neural network (BPNN) model has been developed to predict the wear performance of GCr15 steel. Validation experiments show that the average prediction error for the BPNN model is 10.64%. Full article

During the maintenance of railway fasteners, there are issues with the current nut disassembly and assembly operation, including low efficiency, heavy reliance on manual labor, and high physical strain. A mechanical device has been designed to move along the railway track while identifying and locating the center of the nut to perform disassembly and assembly operations. First, based on the nut disassembly and assembly process and the operating environment, the structure of the equipment was designed. This machine can simultaneously disassemble and assemble all the nuts on a single rail tie and accommodate position errors and deviations of spiral spikes. Secondly, to verify the structural reliability of the designed machine, a static simulation analysis was conducted on the key load-bearing structures under extreme operating conditions. Based on the simulation results, a lightweight design was applied to the machine’s carrier platform. The performance of the nut assembly and disassembly mechanism was optimized based on the Kriging model and the Non-dominated Sorting Genetic Algorithm (NSGA-II). The optimized machine reduced its mass by 21.7% and increased its strength by more than 30%. A transient analysis was also conducted on the optimized machine structure, further validating its strength. Finally, based on the design and optimization results, a physical prototype of the nut disassembly machine was constructed and tested. The results show that the device can efficiently perform nut disassembly and assembly tasks on the railway track. Both the mechanical structure’s reliability and functionality meet the design objectives and requirements, demonstrating significant application value for promoting the intelligent maintenance of railways. Full article

Tracing the root cause of defective products in liquid storage tank (LST) production poses a formidable challenge due to the complex dependencies between production and inspection processes. With associated coupling existing among multiple production processes, and the correspondence between the faults in production processes and inspection links being non-unique, these faults are usually difficult to be directly located via a single inspection process. In this paper, the problem of tracing the root cause of defective LST products, which is caused by process parameter deviations or human operation errors during production, is studied. A root cause tracing method that is based on the dynamic multi-fault diagnosis (DMFD) framework is proposed. First, a factorial hidden Markov model (FHMM) is established to depict the state transition process of the LST product, where its status changes over time and across production processes. This is achieved by considering the product state at each production process as a hidden state and the outcomes of each inspection process as an observation state. Then, the Viterbi algorithm is employed to solve the hidden state transition matrix and diagnostic matrix within the framework of the FHMM. Finally, experimental verification is carried out on a real LST assembly production line, and the influence of imperfect testing on the model accuracy is also considered. The experiment is carried out on an LST assembly line that encompasses three discrete links, including the welding of the upper and lower bodies, the installation of check valves, and the installation of sensors. Experimental results demonstrate that the proposed method achieves significantly more superior performance when compared to existing algorithms. Full article

Splined assemblies ensure precise torque transmission and alignment in mechanical systems. Three-dimensional printing, especially FDM, enables fast production of customized components with complex geometries, reducing material waste and costs. Optimized printing parameters improve dimensional accuracy and performance. Dimensional accuracy is a critical aspect in the additive manufacturing of mechanical components, especially for splined shafts and hubs, where deviations can impact assembly precision and functionality. This study investigates the influence of key FDM 3D printing parameters—layer thickness, infill density, and nominal diameter—on the dimensional deviations of splined components. A full factorial experimental design was implemented, and measurements were conducted using a high-precision coordinate measuring machine (CMM). To optimize dimensional accuracy, artificial neural networks (ANNs) were trained using experimental data, and a genetic algorithm (GA) was employed for multi-objective optimization. Three ANN models were developed to predict dimensional deviations for different parameters, achieving high correlation coefficients (R² values of 0.961, 0.947, and 0.910). The optimization process resulted in an optimal set of printing conditions that minimize dimensional errors. The findings provide valuable insights into improving precision in FDM-printed splined components, contributing to enhanced design tolerances and manufacturing quality. Full article

This study introduces an optimization design method for large-scale curvature-adjustable optical mirrors, innovatively integrating parametric modeling with the optimized layout of actuators, targeting the achievement of extensive curvature adjustability and high-precision surface correction for segmented mirrors. The optimization objective is based on the surface figure residual when the curvature radius of the segmented mirror is altered by 100 mm. Through the optimization of the number, arrangement, and thickness of reinforcement ribs of the actuators on the back of the segmented mirror, a parametric model of a segmented mirror with an edge-to-edge distance of 510 mm and a radius of curvature 9100 mm is developed. Simulation outcomes reveal that a 0–15 μm variation in the actuators results in a curvature radius change of 178.45 mm in the segmented mirror, with a highly linear correlation, achieving a radius of curvature reconfiguration of the primary mirror in the optical system from 9100 mm to 9000 mm, with a residual surface figure error of less than 10 nm. The experimental results indicate that within a 0–15 μm closed-loop stroke range, the curvature radius of the segmented mirror can be adjusted by 146.89 mm, fulfilling the design objective of a lightweight mirror with a significantly adjustable curvature radius. This research is anticipated to offer technical support and serve as a reference for the assembly, adjustment, and inspection of large-aperture segmented mirrors, as well as for the curvature radius variation in multiple segmented mirrors, thereby holding substantial practical value in engineering applications. Full article

To overcome the limitations imposed by the low flexible angle of conventional robots, an active–passive variable stiffness elastic actuator (APVSA) is investigated and a nonlinear dynamic model for the APVSA is established, considering the factors of the moment of inertia, stiffness and damping of elastic elements, meshing stiffness of gear systems, nonlinear backlash, nonlinear meshing damping, and comprehensive transmission error. The established dynamic model is discretized by the forward Euler method, and the variable stiffness performance and the influence of nonlinear factors on the APVSA are analysed by Adams and Simulink simulations, respectively. A physical prototype and an experimental platform were assembled, and the dynamic and static variable stiffness experiments were conducted. The experimental results realized the expected stiffness adjustment target and provided the foundation for the next step of control. Full article

The hybrid laser inertial navigation system (INS) is increasingly vital for high precision under high-dynamic, long-duration conditions, especially in complex aircraft environments. Key components like the base, platform, and inner/outer frames significantly impact system accuracy and stability through thseir static and dynamic characteristics. This study focuses on minimizing deviations in the INS body coordinate system caused by elastic deformation under high overload by developing a mechanical simulation model of a rotational modulation structure and a structural model of the outer frame assembly. A reliability analysis model is established, considering both functional and structural strength failures. To address uncertainties from manufacturing, technical conditions, material selection, and assembly errors, a global sensitivity analysis based on Bayesian inference evaluates parameter contributions to functional failure probability, using a sample size of N1 = 5 × 10⁵. Additionally, uncertainty analysis via Sobol sequence sampling (N2 = 10,000) examines the impact of mean design parameter variations on failure probability for ZL107 and SiCp/Al aluminum matrix composite frames. Experimental verification concludes the study. The results indicate that the SiCp/Al composite material demonstrates superior mechanical performance compared to traditional materials such as the ZL107 aluminum alloy. The uncertainties in the inner frame thickness, inner frame material strength, and outer frame thickness have the most significant impact on the probability of functional failure in the hybrid INS, with sensitivity indices of ${\delta }_6^{P\left\{F\right\}}$ = 0.01657, ${\delta }_2^{P\left\{F\right\}}$ = 0.00873, and ${\delta }_4^{P\left\{F\right\}}$ = 0.00818, respectively. The mechanical properties of the outer frame structure made from SiCp/Al are significantly enhanced, with failure probabilities across three failure modes markedly lower than those of the ZL107 frame, indicating high reliability. In an impact test conducted on the product, the laser gyroscope worked normally, the hybrid laser system function was normal, and the platform angular velocity change corresponding to each impact direction was less than 12 ″/s. The maximum angle change of the inner and outer frames was 0.107°, indicating that the system structure can withstand large overloads and multiple levels of mechanical environments and has good environmental adaptability and reliability. This analytical approach provides a valuable method for reliability evaluation and design of new hybrid INS structures. More importantly, it provides insights into the influence of design parameter uncertainties on navigation accuracy, offering critical support for the advancement of inertial technology. Full article

Electromagnetic force installation is recognized as a viable solution for interference-fit issues in large-diameter bolts. However, the dynamic mechanical behavior of the joint during installation has not been fully clarified. This study investigated the dynamic mechanical behavior of large-diameter Ti/Ti interference-fit bolted joints during electromagnetic installation through numerical simulation and experimental validation. The simulation results indicate uniform deformation at the inlet of the bore wall under interference levels, with a maximum displacement variance of 21.1 μm². Axial stress distribution exhibited higher uniformity at 1% and 1.5% interference-fit amounts, demonstrating the capability of the electromagnetic-driven installation technique to ensure high-quality assembly within a defined interference range. The inlet-end stress consistently exceeded the outlet-end stress, while excessive interference (>1%) induced localized plastic deformation at the upper/lower plate inlets due to material softening. The critical interference threshold of 1% was identified: elastic deformation dominated below 1%, transitioning to plastic deformation beyond this limit. Thus, 1% interference is optimal for a Φ9.98 mm TC4 laminated structure. Furthermore, simulation and experimental results showed strong agreement, with installation force errors below 3.71%, validating the reliability and accuracy of the model in predicting dynamic interference-fit behavior. Full article