Search Results (869)

When acquiring point cloud data of precision parts using 3D scanning devices, occlusion or equipment limitations often lead to sparse and incomplete data, resulting in the distortion or loss of key geometric features. To address this issue, this study proposes an attention-enhanced feature-based point cloud completion network for precision parts, using precision bearing rings as an example to construct a dedicated completion dataset for training. The proposed network adopts an encoder–decoder architecture. In the encoder stage, a curvature-weighted sampling feature extraction module and spatial attention mechanism are introduced to extract both local and global features from the incomplete point cloud, followed by multilevel feature fusion. The multiscale features extracted by the encoder are then fed into the decoder, which hierarchically and progressively predicts the missing regions of the point cloud. Finally, an adversarial generation module incorporating a biased attention mechanism enhances the sensitivity of the network to geometric structural differences, thereby producing a complete and refined point cloud as the final output. Experimental results show that on the ShapeNet-part dataset, the proposed network achieves average CD, Pred → GT, and GT → Pred errors of 4.663, 2.459, and 2.457, respectively, representing reductions of 10.8%, 4.7%, and 8.1%, respectively, compared with the mainstream PF-Net completion network. On the bearing ring dataset constructed in this study, the average CD, Pred → GT, and GT → Pred errors were 0.497, 1.064, and 0.601, respectively, decreasing by 9.3%, 16.3%, and 16.2%, respectively, relative to PF-Net. Moreover, the proposed network effectively completed the point clouds of various missing parts, demonstrating its robustness across different types of precision parts. Full article

Ferrofluid sealing is an important non-contact sealing technology for ultra-high vacuum (UHV) equipment, but its reliability is affected by more than pressure-bearing capacity alone. This review shows that carrier-liquid evaporation, material outgassing, thermal degradation, magnetic-field distortion, and liquid-ring instability are the main factors limiting UHV ferrofluid seals. Multiphysics simulation and parametric optimization remain the most mature tools for analyzing magnetic-field distribution, pressure resistance, temperature rise, and structural deformation. Data-driven condition identification improves failure monitoring, whereas physics-informed neural networks, topology optimization, and multi-objective optimization are still emerging methods for low-sample prediction and collaborative design. Future studies should focus on low-vapor-pressure ferrofluids, bake-out compatibility, thermal management, lifetime prediction, and integrated model–data design frameworks. Full article

Rub-impact is a critical failure mode in high-speed rotor systems that heavily complicates fault diagnosis. While traditionally studied in aero-engines due to its severe risks of blade damage and thermal-induced rotor instability, rub-impact has increasingly emerged as a crucial concern in modern electric vehicle (EV) traction motors characterized by high speeds, slender shafts, and ultra-narrow rotor–stator air gaps. Since rub-impact rarely occurs in isolation, this study establishes a dynamic model of an EV motor rotor system experiencing compound rub-impact and bearing faults based on Jeffcott rotor theory and the lumped-mass method. The influences of key fault parameters on system dynamics are comprehensively investigated through analyses of time histories, phase trajectories, Poincaré sections, frequency spectra, and envelope spectra. The results show that increasing the rub-impact stiffness (from 1.0 × 10¹⁰ N/m to 3.0 × 10¹⁰ N/m) significantly enhances the non-linear impulsive behavior of the system while reducing the rotor unbalance vibration amplitude by 20.0%. Under compound fault conditions with a local bearing defect width of 3 mm, the disk response is mainly governed by global rub-impact behavior, whereas the bearing-end response is more sensitive to local bearing defects. Under compound fault conditions, although widening the localized bearing defect (from 1 mm to 3 mm) significantly exacerbates the local fault severity at the bearing end, the disk’s phase trajectories, Poincaré maps, and spectra remain virtually uninfluenced. This is attributed to the fact that the relative signature intensity of the bearing fault characteristic frequency $f_i$ attenuates by more than 99% during structural transmission, causing the global non-linear dynamics of the rotor disk to be exclusively governed by global rub-impact behavior and completely insensitive to the localized defect propagation. These quantitative findings provide a precise theoretical basis for the diagnosis and identification of compound faults in rotor systems. Full article

Accurate quantitative diagnosis of spall sizes in rolling bearings is often hindered by the limitations of conventional dynamic models in characterizing temperature-dependent contact behavior. To address this issue, this paper presents a quantitative diagnosis method that incorporates point-contact thermo-elastohydrodynamic lubrication (TEHL) characteristics into a classical bearing dynamic framework. Specifically, rather than using prescribed or constant contact parameters, an improved equivalent stiffness–damping representation of the bearing contact interface is formulated based on TEHL-derived oil-film pressure, thickness, and temperature, while taking into account the inner–outer raceway thermal asymmetry. This localized lubricated contact representation is subsequently integrated into a classical five-degree-of-freedom (5-DOF) dynamic model to evaluate the double-impact response caused by outer-ring spalls. Comparative simulations using conventional 5-DOF, 4-DOF, and 2-DOF models, alongside experiments on a 6205-2-RS bearing with a 0.6 mm outer-ring defect, validate the proposed method. The results demonstrate that utilizing the TEHL-derived stiffness–damping representation significantly reduces spall-size estimation errors, improving both the accuracy and the physical interpretability of bearing fault quantification under thermally coupled conditions. Full article

Auxiliary bearings in vertical magnetic suspension systems can suffer thermal damage and impact-induced failure during rotor drop events caused by instability. This study aims to clarify the coupled effects of collision, frictional heating, and transient heat transfer on auxiliary bearing response. Dynamic, thermodynamic, and finite element models were established to analyze impact behavior, frictional heating, and temperature-field evolution, and were validated using rotor-drop measurements of impact force, rotor displacement, and outer-ring temperature together with post-test damage observations. The results show that severe impact and friction rapidly convert rotor kinetic energy into thermal energy, producing a non-uniform temperature field in the auxiliary bearings. The highest temperature occurs in the inner ring, followed by the rolling elements and outer ring, with peak temperatures of 169.59 °C, 154.66 °C, and 94.79 °C, respectively. Owing to gravity, gyroscopic motion, and rotor inclination during drop, the upper auxiliary bearing experiences greater impact loads, a faster speed increase, and a higher peak temperature rise than the lower bearing. Experimental evidence, including thermal discoloration, wear positions, and component damage, agrees with the simulated high-temperature regions. These results support thermal-shock-resistant design, structural optimization, and operational safety assessment of auxiliary bearings. Full article

The collaborative load-bearing behavior between the rock mass and support is critical for tunnel support design. This study proposes a strain-softening analysis method for circular tunnels during construction and presents an efficient solution strategy, termed the “Support Load Approximation Strategy” (SLAS), to solve the collaborative load-bearing problem. The rock mass is assumed to be isotropic, following the Mohr–Coulomb criterion, under hydrostatic stress conditions. During the stepwise calculation, a new ring is automatically added at each step, and the positions of all previous rings are updated, with elastic or plastic formulations automatically selected based on the state of each ring. The GRC and plastic radii (R_p and R_s) curves obtained by the proposed method show excellent agreement with existing benchmark results, with relative errors of 3.73% for the GRC, 1.47% for R_s, and 3.40% for R_p, confirming the correctness and accuracy of the proposed algorithm. Furthermore, when compared to the Incremental Support Load Method (ISLM) and the binary search method, SLAS improves computational efficiency by 14.2 times and 67%, and accuracy by 70% and 53%, respectively. When higher precision is required, SLAS maintains an efficiency gain of 82.8 times over ISLM with comparable accuracy. Compared to traditional elastic-plastic analysis methods, the proposed approach simplifies the computational process, reduces complexity, offers both high accuracy and fast computation speed, and serves as a practical tool for tunnel engineering support design. Full article

Existing component-based models have difficulty interpreting the field response of earth pressure balance (EPB) shield tunneling parameters when the excavation face gradually changes from hard rock to sandy strata. To address this problem, this study proposes a mechanism-informed semi-empirical analysis based on a continuous face sand fraction function, $\eta \left(z\right)$, which represents the evolution of the sand-bearing area fraction at the excavation face along the shield advance direction. The function is constructed from the geological profile and is used as a continuous reformulation of existing face-composition descriptors such as rock/sand ratio and composite ratio. Based on $\eta \left(z\right)$, engineering-equivalent models for total thrust and cutterhead torque are developed and evaluated using field tunneling data from Qingdao Metro Line 15 and Line 5. The Dandan right-line data are used for parameter calibration, while the Basi right-line data from Rings 590–650 are used for independent validation without further parameter tuning. The results show that the η-related correction term improves the independent validation performance of the total thrust model, reducing the MAPE from 22.56% to 14.25%. In contrast, cutterhead torque exhibits stronger operational variability and interval-specific baseline offset. After applying a baseline correction determined from the stable hard-rock section of the Basi interval, the ring-scale torque MAPE decreases from 44.07% to 17.25%, but the additional $\eta$-related torque contribution remains limited. These results indicate that total thrust is more sensitive to the gradual increase in face sand fraction, whereas cutterhead torque is more strongly influenced by machine condition, cutter wear, and operational control. The proposed approach provides a field-based semi-empirical reference for interpreting tunneling parameter responses in similar hard-rock-to-sandy-strata transition zones. Full article

Hydrogen-compatible elastomeric seals are critical for the reliability and safety of high-pressure hydrogen infrastructure. However, hydrogen exposure can alter the mechanical response and surface condition of elastomeric materials through coupled transport–mechanical interactions. This study presents a comparative experimental and data-driven investigation of the pressure-dependent degradation behavior of ethylene propylene diene monomer (EPDM), nitrile butadiene rubber (NBR), and fluorocarbon elastomer (FKM) O-ring seals following 192 h exposure to hydrogen pressures ranging from 800 to 7000 psi at room temperature. Tensile testing was performed directly on complete O-ring geometries, and descriptor-based analysis was used to quantify peak-response behavior, energy absorption, stiffness evolution, and normalized deformation characteristics. Multivariate statistical methods, principal component analysis (PCA), clustering analysis, and Random Forest regression were applied to identify material-specific degradation patterns. NBR maintained the highest overall load-bearing capability and stiffness-related response across the investigated pressure range, whereas EPDM exhibited more compliant and non-monotonic deformation behavior. FKM showed the strongest pressure sensitivity, with substantial increases in force- and stiffness-related descriptors at elevated hydrogen pressures. Optical image analysis revealed pronounced increases in defect density and defect area fraction for NBR, while FKM exhibited comparatively stable surface-state behavior. PCA and clustering analyses identified distinct material-dependent degradation trajectories, and Random Forest regression achieved an R² value of 0.888 for energy-absorption prediction. The results demonstrate that hydrogen-induced degradation emerges through coupled interactions among stiffness evolution, deformation progression, energy absorption, and surface-state changes, providing a comparative framework for assessing elastomer performance in hydrogen environments. Full article

When the magnetic field of a magnetic levitation bearing is lost, the cage-less ball bearing acts as a backup bearing to support the falling spindle. To ensure uniform distribution of the rolling elements in the cage-less ball bearing, researchers have designed local functional grooves on the outer ring raceway. However, the periodic motion of the rolling elements causes damage to these grooves, leading to discrete failure of the rolling elements and resulting in vibration during bearing operation. Therefore, this paper investigates the dynamic characteristics of the rolling elements and the factors influencing bearing vibration following damage to the local functional grooves in caged ball bearings. A vibration model for bearings with damaged functional grooves is established, and the research is conducted through theoretical analysis, numerical simulation, and experimental validation. Full article

The dimensional accuracy of the bearing inner ring is critical for the operational performance and reliability of high-end equipment. However, nonlinear deformation of the measurement mechanism caused by temperature variations and temperature drift of the sensor significantly affect the measurement accuracy. In this study, a novel online measurement system for bearing inner diameter was designed, which integrates a two-degree-of-freedom motion mechanism and an adaptive elastic measurement probe. To compensate for the measurement errors caused by temperature effects in the proposed system, an intelligent compensation method based on a CNN-LSTM–Attention hybrid model was proposed. The raw sensor signals and ambient temperature were used as the model inputs, and an end-to-end nonlinear mapping relationship for the actual bearing inner diameter deviation was established without the need to construct complex explicit physical equations. The experimental results show that, within the investigated temperature interval of 11–21 °C, the proposed method controls the measurement error within 1.87 μm, thereby satisfying the dimensional measurement requirement for P4-grade bearings with a tolerance of 0 to −6 μm. Full article

Background/Objectives: Microtubule-targeting agents represent a pillar of cancer chemotherapy; however, their clinical utility is constrained by significant toxicity, pharmacokinetic instability, and susceptibility to multidrug resistance transporters. This study aimed to explore the impact of replacing substituted phenyl rings with a naphthalene moiety in sulfonamide-based colchicine-site ligands, with the goal of identifying new antiproliferative candidates with improved profiles. Methods: We designed, synthesized, and evaluated a library of 35 naphthalene sulfonamides bearing varied aryl groups and sulfonamide nitrogen substituents. We assessed the antiproliferative activity against multiple cancer cell lines. Mechanistic studies, including fluorescence microscopy, cell cycle analysis, and cell death assays, were performed to evaluate the effect of these compounds on microtubule polymerization dynamics and cell fate. Molecular docking and in silico pharmacokinetic profiling were carried out to support the proposed binding mode at the colchicine site and to assess drug-likeness. Results: Exclusively, compounds bearing a trimethoxyphenyl group showed antiproliferative activity in the submicromolar range, thus identifying it as a structural requirement. The most potent compound (2) reached double-digit nanomolar IC₅₀ values (67–104 nM) across multiple cancer cell lines. Microscopy confirmed intracellular disruption of microtubule polymerization. Unlike colchicine, these compounds did not induce canonical mitotic arrest but instead triggered apoptotic cell death. In silico analyses supported binding at the colchicine site and revealed favorable predicted pharmacokinetic properties. Conclusions: The naphthalene sulfonamides described herein demonstrate potent antiproliferative activity through a distinct mechanism compared to colchicine, and their favorable in silico profiles position them as promising candidates for further development as antitumor agents. Full article

This article details the synthesis and structural characterization of a new metalloid germanium cluster 3 with bulky amide ligands. The cluster features a Ge₆ core stabilized by four -N(Si^tBuMe₂)₂ ligands and was obtained via reduction of the amido trichlorogermane 2 using potassium chips in toluene. Single-crystal X-ray diffraction analysis revealed that the Ge₆ core adopts a butterfly-shaped geometry with a Ge-Ge dumbbell unit, which contains two unsubstituted germanium atoms exhibiting prominent lone-pair characteristics. The Ge₆ core can also be classified as a nido cluster, with a cluster-bonding-electron count of 16, perfectly satisfying the 2n + 4 electron-counting rule. Combining the structural features of this nido cluster with the bond length distribution in the folded four-membered ring suggests that the Ge4 ring features a certain degree of electron delocalization. Additionally, two bis(amido)-substituted germylenes (4 and 6) were isolated and structurally characterized. They exhibit analogous structural features, with each germanium center adopting a two-coordinate V-shaped configuration, the Ge–N bond lengths being very similar, and the nitrogen atoms adopting a planar triangular geometry. Notably, compound 6, bearing bulkier -N(SiⁱPr₃)₂ substituents, exhibits a significantly larger N-Ge-N bond angle (120.58°) compared to the corresponding value of 113.54° observed for compound 4 with -N(Si^tBuMe₂)₂ substituents. This clearly demonstrates that the steric bulk of the substituents exerts a remarkable influence on the molecular geometry and σ-donor ability of the lone pairs on germanium centers. Full article

This study investigates the quasi-static mechanical behavior of a flexible anti-collision ring (FACR) for bridge protection through axial tests and finite element (FE) simulations. The FACR features a multi-layer steel wire rope coil (SWRC) encased in a chloroprene rubber matrix. Quasi-static tensile and compressive tests (80 mm/s) were conducted on both the SWRC and the FACR, with full-field strain distributions captured via digital image correlation (DIC). The results demonstrate that the rubber matrix significantly enhances load-bearing capacity (by 200% in compression and 337% in tension) and energy dissipation (by 403% and 620%, respectively), with bending identified as the dominant deformation mode. An FE model was developed and validated against experimental data, then employed for parametric analysis. The cross-sectional ratio, governed by the number of SWRC layers, exhibits a strong nonlinear influence on the tensile response, and a three-layer configuration is identified as optimal, achieving the highest energy absorption without compromising compressive performance. A layer-dependent mechanism analysis reveals that excessive layers lead to a drastic stiffness reduction in outer coils, impeding coordinated load sharing. Building upon this mechanism, an optimized two-layer arrangement maximizing the inner-layer SWRC proportion is proposed, achieving 2.0× and 1.9× improvements in peak tensile force and energy dissipation, respectively, while using fewer steel wires. This work provides a fundamental understanding and an efficient optimization strategy for FACRs. Full article

Rockburst is one of the major geological hazards in the construction of deep-buried and high-geotemperature tunnels. Using triaxial compression tests and acoustic emission (AE) techniques, this paper conducts a preliminary exploratory investigation on the deformation and failure characteristics, mechanical parameters, acoustic emission responses and energy evolution laws of typical rockburst-prone rocks under confining pressures of 10–30 MPa and temperatures of 100–250 °C. The results show that within the research scope, sandstone exhibits brittle characteristics including compaction, linear elasticity, crack initiation and propagation, stable crack propagation stage, accelerated crack propagation stage, and stress drop stage. Within a certain range, peak strength and damage strength increase with the rise in confining pressure and temperature. The elastic modulus increases with rising confining pressure. The damage point may be the critical point of energy conversion and acoustic emission activity. After damage, the work done by external forces is mainly converted into dissipated energy. With the intensification of surrounding rock damage, the ratio of elastic strain energy to total energy gradually decreases, while the ratio of dissipated energy to total energy gradually increases. Acoustic emission activity increases significantly at the damage point and reaches its peak at the peak strength. The cumulative acoustic emission ring count and cumulative energy increase slowly before the peak and grow rapidly after the peak. Under thermo-mechanical action, new cracks in sandstone preferentially initiate along grain boundaries, and the inconsistent deformation between grains will promote the formation of transgranular cracks. The connection, convergence and final penetration of cracks lead to sample failure. The elevation of temperature and confining pressure can enhance the bearing capacity of sandstone, indicating that a high-temperature and high-stress environment may be conducive to the occurrence of rockbursts. The research results provide scientific support for an in-depth understanding of the mechanical behavior and instability risk of rockburst in deep-buried and high-geotemperature tunnels, and can provide a theoretical basis for rockburst prevention and control of high-geotemperature tunnels of the CZ Railway. Full article

To address fault diagnosis under limited sample conditions, this paper proposes a small-sample diagnosis framework integrating multibody dynamic modeling and a GAN–CNN fusion strategy. First, a rigid–flexible coupled multibody dynamic model of the reducer is established to simulate vibration responses under typical fault modes, including broken gear tooth, gear wear, and bearing outer ring fault, thereby generating representative simulation samples. Second, to reduce the distribution discrepancy between simulated and measured data, the simulated samples are introduced into a generative adversarial learning framework for feature enhancement, with limited measured samples used as references. Cosine similarity is employed to evaluate the consistency between the enhanced simulated data and the measured data in the feature space. Finally, the enhanced simulated samples are fused with measured samples to construct a hybrid dataset for convolutional neural network training and fault classification. Experimental results show that the proposed framework improves the similarity between simulated and measured data, with cosine similarity increasing from below 0.65 to above 0.80. Under small-sample conditions, the mean diagnosis accuracy reaches 83.81%, which is 17.33 percentage points higher than that obtained using the original small-sample dataset. The proposed framework provides an effective modeling and algorithmic approach for reducer fault diagnosis under data-scarce conditions. Full article