ObjectiveAs the core component of a wind turbine pitch system, pitch bearings must endure complex fatigue loads generated by blades throughout their entire life cycle. Cracking at the plugging hole is one of the most common failure modes. To address this issue, the stress components driving the failure were analyzed, the potential reasons for the actual service life being shorter than the design simulation results were pointed out, and an on-site rectification scheme was proposed for engineering application practices.MethodsFirstly, the macroscopic morphology of the crack fracture at the plugging hole was analyzed to preliminarily identify the damage type. Secondly, a global finite element model (FEM) of the entire pitch system and a sub-model of the plugging hole were established and solved. The stress state and fatigue life at the plugging hole were evaluated, and the direction of the driving stress causing the crack was identified. Thirdly, considering the actual manufacturing process and fracture observation, the influence of surface scratches on the bearing life was discussed. Finally, an on-site rectification scheme involving the installation of a flange at the plugging hole was proposed, and its feasibility was analyzed using the FEM.ResultsThe results demonstrate that the circumferential stress along the intersection line between the plugging hole and the pin hole acts as the driving factor for the fatigue life of the plugging hole. During the bearing manufacturing process, surface defects such as scratches significantly reduce the bearing life. The rectification scheme using an additional flange not only substantially extends the bearing life but also features low cost and easy implementation. This study provides a methodological reference for ring fatigue assessment during the pitch bearing design phase, offers process control recommendations for practical production, and presents a feasible solution for risk mitigation in operational wind turbines.
ObjectiveChallenges including filtering distortion, outlier interference and non-stationary component resolution exist in gear tooth surface waviness extraction, and conventional approaches fail to achieve both geometric fidelity and high spectral resolution. A robust method for waviness extraction and spectral characterization along gear feature lines was proposed.MethodsFirstly, normal deviation signals were constructed along gear feature lines and detrending processing was completed, so as to realize one-dimensional dimensionality reduction of three-dimensional tooth surface errors and provide a unified geometric benchmark for waviness separation. Secondly, a robust Gaussian regression filtering model was established, and M-estimation and biweight iterative mechanism were introduced to suppress boundary distortion and spike interference and ensure the geometric fidelity of main waviness morphology. Then, adaptive multi-scale decomposition of the filtered signals was performed using CEEMDAN-HHT, and a space-frequency-energy characterization framework was constructed to analyze the multi-scale features of non-stationary waviness components. Finally, comparative tests were conducted based on simulation and measured data to quantitatively verify the filtering performance and characterization accuracy of the method.ResultsThe results show that compared with the standard Gaussian filter, the robust Gaussian regression filter improves the outlier suppression capability from 1.13 dB to 5.0 dB and reduces the boundary error by about 80%. Compared with FFT, CEEMDAN-HHT reduces the reconstruction root mean square error from 0.70 μm to 0.63 μm. The adaptability of the method under complex interference is verified by measured data, and local transient waviness defects and global dominant undulations can be clearly identified, which provides reference for quantitative evaluation and cause tracing of gear tooth surface waviness.
ObjectiveA shipborne 6-degree-of-freedom (DOF) parallel platform can compensate for the 6-DOF motions generated by vessels, thereby improving the reliability and safety of offshore operations and extending the operational time window. Such platforms possess advantages including a large workspace, high load-carrying capacity, and low susceptibility to singularities within the workspace. For shipborne application scenarios, a multi-scale comprehensive study was conducted with the F-norm condition number, natural frequency, and stiffness index selected as optimization objectives.MethodsFirstly, the required workspace of the 6-DOF parallel platform was analyzed based on the motion response of ships at sea, and this workspace was used as a constraint for the dimensional synthesis of the mechanism. Secondly, considering the practical requirements of high response speed, high frequency response, and high precision for shipborne 6-DOF parallel platforms, the F-norm condition number, natural frequency, and stiffness were adopted as multi-objective optimization performance indices to analyze the influence of mechanism parameters on these indices. Thirdly, the non-dominated sorting genetic algorithm Ⅱ (NSGA-II) was employed for multi-objective optimization, and the optimal mechanism parameters for the shipborne 6-DOF parallel platform were selected from the obtained Pareto-optimal set. Finally, simulation verification was carried out.ResultsThe simulation results demonstrate that, under the same control gain, the optimized parameters of the 6-DOF parallel platform achieve superior compensation performance. The residual motion amplitudes along the X, Y, and Z directions and around the X, Y, and Z axes are reduced by 44.6%, 66.7%, 65.6%, 70.5%, 26.3%, and 40.1%, respectively.
SignificanceAiming at the strict requirements for lubrication performance of face gear transmission in helicopter transmission systems, as well as the problems that the analysis system of tooth surface contact-lubrication coupling characteristics in existing research needs to be improved and the engineering application technical path is not clear, the research progress of face gear lubrication technology was systematically sorted out, and the core technical direction and development trend were clarified. [Analysis] Firstly, the research context of face gear lubrication technology for helicopter transmission scenarios was sorted out, and the core research boundary of this field was defined; secondly, the core technology of tooth surface contact characteristic analysis of face gear was disassembled to provide key input parameters for lubrication characteristic analysis; thirdly, the analysis methods and research results of tooth surface lubrication characteristics of face gears were summarized to clarify the key influencing factors of lubrication performance; finally, combined with the engineering requirements of helicopter transmission, the future key development directions of this field were prospected.
SignificanceOriented to the supporting and mounting struts of helicopter final drive, the technical development status of periodic and intelligent struts was explored based on the evolution trend of strut structure. [Analysis] Firstly, the layout configurations for mounting and supporting of the helicopter final drive was introduced. Secondly, the structural characteristics and applicable scopes of each mounting and supporting layout were summarized and analyzed. Finally, combined with typical aircraft cases, the application status of various mounting and supporting layouts in conventional single-rotor helicopters and coaxial twin-rotor helicopters was concluded. [Prospect] It is proposed that the collaborative optimization of lightweight materials and intelligent algorithms will serve as a vital approach to improve the dynamic performance of support systems in the future.
SignificanceThe critical importance of harmonic reducers was elucidated for space deployable mechanisms such as antennas, solar arrays, and robotic arms. A comprehensive review of the research progress was provided on harmonic reducers used in domestic and foreign spacecraft from four perspectives: tooth profile design, wave generator structural design, material selection, and lubrication methods. [Analysis] The advantages, disadvantages, and applicable working conditions of different tooth profile types for the rigid and flexible wheels in space harmonic reducers were summarized, including involute tooth profiles, circular arc tooth profiles, and other forms, and methods for tooth profile modification was introduced. Several design approaches were categorized for wave generator structures, including elliptical cams, dual-disc types, and composite curve cams. The material selection and common material grades for space harmonic reducers were presented, elaborating on the role of heat treatment processes. Furthermore, three primary lubrication methods were summarized for space harmonic reducers, grease lubrication, solid lubrication, and solid-liquid composite lubrication, detailing the pros and cons of each method along with commonly used lubricants in space applications. In response to the development trends of high load capacity and extended service life for space harmonic reducers, future research priorities and developmental directions were proposed.
ObjectiveInternal gear polish honing of aeronautic cylindrical gears can improve tooth surface quality and reduce transmission noise. A forward prediction method for three-dimensional surface roughness suitable for polish honing conditions was established to address the shortcomings of existing honing roughness prediction models, which can only characterize two-dimensional features and ignore the elastic compliance of honing wheels, and to provide support for process parameter optimization.MethodsFirstly, the cutting depth and cutting times of abrasives driven by process parameters were derived based on conjugate meshing rules and abrasive cutting mechanism to provide parametric basis for quantitative calculation of material removal. Secondly, the progressive removal of micro-asperities on tooth surfaces by abrasives was equivalent to a “meshing contact-material removal” signal processing operator of three-dimensional height field to realize accurate mathematical characterization of the machining process. Then, adaptive denoising and morphology-preserving correction were performed on the measured initial tooth surface to restore the real initial machining topography. Finally, iterative calculation of post-honing tooth surface height data was carried out with Matlab software to complete the quantitative prediction of three-dimensional surface roughness.ResultsThe results show that the average prediction errors of arithmetical mean height, root mean square height, and maximum height are 6.42%, 5.29%, and 5.86%, respectively, and the maximum prediction error is less than 12.77%. The surface roughness decreases with the increase of honing wheel speed and increases with the increase of cutting rate. The proposed method can provide references for process optimization of internal gear polish honing and precision machining of complex curved surfaces.
ObjectiveDuring the grinding of helical gears with helical crowning, tooth flank twist defects frequently occur, which degrade tooth flank accuracy and transmission performance. Accordingly, an anti-twist grinding method using variable-lead worm grinding wheels was proposed for helical gears with helical crowning.MethodsFirstly, the instantaneous contact lines between the worm grinding wheel and the helical gear were calculated based on their meshing relation, and the tooth flank inclination deviation and tooth flank twist at different tooth width positions were obtained. Secondly, a variable-lead dressing motion model between the dressing roller and the compensation section of the worm grinding wheel was established according to the calculated twist values at three measurement positions. Finally, the calculation algorithm of tooth flank twist and the dressing motion algorithm of the roller were integrated into the numerical control system to develop a numerical control dressing program for variable-lead worm grinding wheels.ResultsThe results show that after twist compensation, the twist of the left and right tooth flanks is reduced by 93.6% and 81.4%, respectively, which verifies the effectiveness of the proposed twist compensation algorithm.
SignificanceThe critical importance of harmonic reducers was elucidated for space deployable mechanisms such as antennas, solar arrays, and robotic arms. A comprehensive review of the research progress was provided on harmonic reducers used in domestic and foreign spacecraft from four perspectives: tooth profile design, wave generator structural design, material selection, and lubrication methods. [Analysis] The advantages, disadvantages, and applicable working conditions of different tooth profile types for the rigid and flexible wheels in space harmonic reducers were summarized, including involute tooth profiles, circular arc tooth profiles, and other forms, and methods for tooth profile modification was introduced. Several design approaches were categorized for wave generator structures, including elliptical cams, dual-disc types, and composite curve cams. The material selection and common material grades for space harmonic reducers were presented, elaborating on the role of heat treatment processes. Furthermore, three primary lubrication methods were summarized for space harmonic reducers, grease lubrication, solid lubrication, and solid-liquid composite lubrication, detailing the pros and cons of each method along with commonly used lubricants in space applications. In response to the development trends of high load capacity and extended service life for space harmonic reducers, future research priorities and developmental directions were proposed.
Objective15Cr14Co12Mo5Ni alloy is a new type of low-carbon high-alloy steel featuring high strength, high temperature resistance and excellent wear resistance, which is widely adopted in high-end fields such as aerospace and automotive transmissions. Magnetic particle inspection plays a vital role in quality inspection of components made from this alloy. However, the occurrence of short rod-shaped magnetic traces frequently interferes with inspection results. Investigating the formation mechanism of short rod-shaped magnetic traces and analyzing their correlations with the internal microstructure, carbide distribution and forging process of the alloy can provide basis for optimizing forging procedures, controlling grain size, restraining excessive development of dislocation slip bands and reducing interference from magnetic traces.MethodsSpecimens with and without magnetic traces on the shaft bore of alloy gears were selected. Combined with magnetic particle inspection, scanning electron microscopy, metallographic observation and energy dispersive spectroscopy analysis, comparative research on morphological characteristics of magnetic traces, carbide compositions and grain structure differences was carried out from both macroscopic and microscopic perspectives.ResultsMacroscopic and microscopic analyses reveal that the formation of short rod-shaped magnetic traces is closely associated with the clustered distribution of Cr-Mo carbides inside the alloy. Such carbides generate magnetic leakage fields by altering local magnetic permeability, leading to the accumulation of magnetic particles. Further research clarifies the microstructure evolution chain for short rod-shaped magnetic traces, which can be summarized as: coarse grains → dislocation slip bands → Cr/Mo enrichment → directional precipitation along interfaces → carbide banding → magnetic permeability gradient → short rod-shaped magnetic traces.
ObjectiveAs the core component of rotary vector reducers, cycloidal gears rely on high-efficiency and precision machining methods to guarantee the overall performance of reducers. Accordingly, a fundamental method covering the hobbing and grinding processes of cycloidal gears was proposed.MethodsFirstly, meshing equations were derived based on the forming principle of helicoids and spatial coordinate transformation, and geometric motion models for closed tooth profile curves of cycloidal gears, worm cutters and tooth lead modification were established. Secondly, a prototype model of the hobbing-grinding machine tool was constructed using Vericut software to conduct motion simulation of the generated surfaces, followed by comparison with theoretical surfaces.ResultsThe deviation between simulation results and theoretical values is less than 0.004 mm. Hobbing machining test results verify the accuracy of the established theoretical model and the feasibility of the worm cutter hobbing-grinding technology, laying a foundation for high-efficiency continuous tooth profile machining and three-dimensional topological modification of cycloidal gears.
ObjectiveIn the spiral bevel gears of helicopter transmission systems, there exists a problem where gear web fracture occurs due to resonance caused by the proximity between the gear meshing excitation and the inherent traveling wave vibration frequency of the gears. It is necessary to clarify the gear response characteristics under traveling wave resonance to evaluate the gear’s operating performance. To this end, a computational simulation method for the overall structural traveling wave resonance dynamic response of spiral bevel gears was proposed.MethodsBased on the fact that the force acting on the teeth of the driven gear was a spatially periodic function, and following the idea of approximating periodic functions using multiple trigonometric functions, a simulated excitation in the form of a half-sine wave was constructed. The gear was kept stationary, and the traveling wave resonance simulated excitation was applied with consideration of the contact ratio to fit the actual load-bearing state of the gear teeth. The finite element method was used to solve the traveling wave resonance dynamic response of the spiral bevel gear, thereby obtaining the overall structural dynamic response distribution.ResultsResults of dynamic response tests show that, the comparison error between the test results and the simulation calculations is no more than 5.77%, which verifies the effectiveness of the proposed simulation method for calculating the resonance dynamic response distribution of the spiral bevel gear structure. Based on the verified method, the forward traveling wave resonance response of the 4-node diameter of the web is analyzed, and the influence law of the web hole structure on the traveling wave resonance is obtained.
ObjectiveThe time-varying mesh stiffness of gears is influenced by multiple coupled factors, including initial parameters, assembly errors, overlap ratio, wear, and thermo-mechanical coupling effects. To address the ambiguity in applicability boundaries caused by the diversity of existing numerical calculation methods, several typical numerical approaches were systematically elaborated and compared based on the fundamental calculation principles of gear mesh stiffness.MethodsFirstly, a parametric model was established using cylindrical spur gear pairs as the research object. Secondly, a finite element model was constructed based on the parametric model. Thirdly, employing modular object-oriented programming approaches, the selected typical numerical calculation methods (ISO 6336-1: 2019 standard, Ishikawa method, Weber method, and potential energy method) were programmatically implemented. Finally, the finite element model was solved and numerical calculations were performed for each method, followed by comprehensive comparative analysis from multiple perspectives including time-varying mesh stiffness variation patterns, single tooth stiffness, compliance components, average mesh stiffness, and average single tooth stiffness.ResultsThe study reveals that the ISO 6336-1: 2019 standard demonstrates strong engineering applicability but fails to construct a time-varying model. The analytical method and finite element method share similar mechanical principles, yet their relative error reaches 14% due to model simplification and theoretical discrepancies. The compliance calculated by the analytical method exhibits a nonlinear increasing trend from the tooth root to the tip, aligning with mesh deformation patterns and validating its modeling rationality. However, model modifications are required for complex gears or special operating conditions to enhance adaptability.The potential energy method, which accounts for coupled tooth-body deformation, achieves a computational efficiency significantly higher than the finite element method while maintaining an error margin within 1%. This comparative study clarifies the distinctions and commonalities among algorithms, providing guidance for method selection and the development of high-precision, high-efficiency gear stiffness calculation models.
ObjectiveTo address the low prediction accuracy and parameter optimization difficulties of tooth surface roughness for spiral bevel gears, and overcome the limitations of traditional methods in handling complex nonlinear relationships and multivariate coupling effects, machine learning models were adopted to predict the tooth surface roughness of spiral bevel gears.MethodsFirstly, based on the grinding test dataset of spiral bevel gears, three machine learning algorithms including decision tree (DT), support vector regression (SVR) and artificial neural network (ANN) were used to establish roughness prediction models for the convex and concave tooth surfaces, and the prediction performance of the three models was compared. Secondly, multiple linear regression was applied to derive a calculation formula for tooth surface roughness incorporating machining parameters of spiral bevel gears. Finally, Shapley additive explanations (SHAP) were employed to quantify the contribution of each input feature to the predicted roughness, providing references for the application of machine learning in high-performance gear manufacturing.ResultsThe results show that the DT model suffers from underfitting and the SVR model suffers from overfitting, both yielding poor prediction performance. The ANN model achieves excellent data fitting and accurate roughness prediction at the cost of relatively slow computation speed. Its mean relative errors for predicting convex and concave surface roughness reach 3.5% and 6.09%, respectively. The influence degree of each machining input parameter on tooth surface roughness, sorted from highest to lowest, is grinding speed, grinding depth and generating speed.
ObjectiveTo meet the high-quality and high-efficiency manufacturing requirements of spur gears for aviation equipment, conventional single-degree-of-freedom forming processes such as die forging and extrusion suffer from insufficient tooth profile filling and excessive forming load when fabricating aviation spur gears. A novel multi-degree-of-freedom forming concept for aviation spur gears was innovatively proposed. By applying continuous local multi-degree-of-freedom loading via rolling dies, the metal flow capacity was improved and forming load was reduced. Meanwhile, the grain structure of gears was refined, and continuously distributed metal flow lines along the tooth profile were generated, which further enhances gear strength and extends fatigue life, thus provides a new technical route for manufacturing aviation spur gears with high strength, high toughness and long service life.MethodsFirstly, finite element simulation was adopted to investigate the influence law of blank shape on tooth profile filling performance and forming load, based on which an optimized blank design method was proposed. Secondly, the laws of tooth profile filling, distribution and evolution of equivalent strain, as well as the evolution of metal flow lines during forming were revealed. Finally, multi-degree-of-freedom near-net-shape forming process test for aviation spur gears was carried out according to finite element simulation results. Grain size and metal flow line inspections were conducted on test specimens to verify the validity of the above finite element model and simulation results.ResultsThe results indicate that the frustum-shaped blank can effectively improve tooth profile filling and reduce forming load, and aviation spur gear specimens with fully filled tooth profiles are ultimately obtained. Moreover, the multi-degree-of-freedom forming method introduces severe plastic deformation in the tooth profile region, which not only significantly refines gear grains, but also produces continuous metal flow lines following the tooth contour. Accordingly, the multi-degree-of-freedom near-net-shape forming technology enables high-performance manufacturing of aviation spur gears.
ObjectiveIn order to improve the pose accuracy of the 2PSR-PUU parallel machine tool with large swing angle characteristics, related research was conducted on the 2PSR-PUU parallel machine tool as the object.MethodsFirstly, the closed-loop vector method was used to solve the forward and inverse kinematics of the parallel robot. Secondly, an error model for parallel robots was established using partial differential theory, and a quantitative analysis was conducted on the relation between error parameters and the pose accuracy of the moving platform. The error compensation model of the parallel machine tool was established, and the improved particle swarm optimization algorithm was introduced to perform optimization solution of the error compensation function. Finally, simulation analysis of the error model for the parallel robot was carried out in Matlab.ResultsThe simulation and test results show that after error compensation of the parallel machine tool, the order of error of each pose parameter is effectively improved. The maximum error values of the moving platform in the x and z axes and the angle of freedom direction in the φ direction are reduced from 1.614 mm, 1.612 mm, and 0.468° to 0.001 99 mm, 0.001 50 mm, and 0.001 1°, respectively. Moreover, the peak in the pose error curve before and after compensation is improved, proving that the error compensation algorithm can effectively improve the motion stability and pose accuracy of the 2PSR-PUU parallel machine tool.
ObjectiveData-driven fault diagnosis methods frequently encounter the problem of sample imbalance in rolling bearing fault diagnosis. To address this issue, a sample class imbalance augmentation method based on an improved auxiliary classifier generative adversarial network (ACGAN) was proposed, namely the global attention mechanism independent classifier generative adversarial network (GAMICGAN).MethodsFirstly, global attention mechanisms and octave convolutions were introduced, enabling the generator to fully attend to spatial, channel, and dimensional information as well as high- and low-frequency component information in time-frequency images, thereby improving the generation quality of specified class samples. Secondly, to mitigate the decline in diagnostic model accuracy caused by distribution differences in sensor data under varying operating conditions, a domain adaptation fault diagnosis method for bearings based on joint distribution domain adversarial neural networks was proposed. A backbone network structure based on global attention residual networks was designed. Finally, joint maximum mean discrepancy metrics were utilized to quantify marginal and conditional distribution differences between source and target domains, achieving bearing fault diagnosis under varying operating conditions.ResultsThe results indicate that the proposed method maintains high diagnostic accuracy in variable operating condition applications with imbalanced samples and demonstrates robust adaptability to complex scenarios.
ObjectiveWith the booming new energy vehicle industry, higher precision standards are required for automotive gears. To construct a more accurate process parameter model, a multi-process parameter optimization technology for precision gear grinding based on the Levenberg-Marquardt (L-M) algorithm was studies.MethodsFirstly, a self-developed new form gear grinding machine was used as the test platform, and 20CrMnTi gears processed by form grinding were selected as research objects. Four characteristic process parameters were defined: grinding wheel linear speed, axial feed speed of the grinding wheel along the gear, total feed passes of the grinding tool, and single-cut grinding depth. Secondly, uniform design tests were conducted to investigate the influence of each grinding parameter on gear flank machining performance. First-order linear regression analysis was adopted to establish the functional correlation between process parameters and gear flank machining indicators. Finally, the L-M algorithm was applied with full consideration of coupling effects among various grinding factors to realize high-efficiency and high-precision machining of each grinding step.ResultsTest results indicate that the use of four optimized grinding parameters can significantly promote machining efficiency and improve the quality of machined gear flanks.
ObjectiveTo improve the overall performance of collaborative robots and achieve more stable, efficient and precise operation, lightweight design and simultaneous dynamic performance optimization were conducted for integrated joints.MethodsFirstly, the mechanical structure model, transmission system model and frequency characteristics were analyzed. Secondly, a strategy taking joint moment of inertia as the optimization variable was adopted. The rated parameters of fixed components inside the integrated joint, such as the motor and harmonic reducer, were set as constraint conditions of the objective function. The nondominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) was used to comprehensively optimize three key performance indicators, namely the joint resonance frequency, the inherent electrical frequency of the motor and the total joint mass. Finally, material optimization design was carried out for the integrated joint on the basis of the above multi-objective optimization results.ResultsAfter multi-objective optimization, the joint moment of inertia is reduced by 16.6%, and the joint mass is decreased by 15.2%. The results of multi-objective optimization and material optimization are highly consistent, which verifies that the material optimization scheme meets the lightweight design requirements.
ObjectiveDeep learning-based fault diagnosis methodologies typically require substantial volumes of high-quality training data. In response to the prevalent challenge of acquiring authentic bearing fault data, which significantly impedes diagnostic accuracy, a novel simulation data-driven bearing fault diagnosis framework was specifically proposed for small-sample scenarios.MethodsThe simulation data of bearings in different states was obtained by constructing a dynamic model, the simulation data was enhanced based on the conditional channel Wasserstein generative adversarial network with gradient penalty (CCWGAN-GP) model that introduced the channel attention mechanism, and synthetic data that was highly similar to the simulation data was generated to form the virtual data. Finally, the parameters learnt from the virtual data were migrated to the test data by using a migration learning model that was based on the loss of the validation set to make fine adjustments to achieve effective diagnosis of bearing faults under the conditions of small sample test data.ResultsBy using Case Western Reserve University bearing data for tests, the effectiveness of the proposed method is verified. It is shown that the proposed method can achieve excellent fault diagnosis performance under small sample conditions.
