Search Results (232)

This study proposes a canopy-adaptive TAD-IRRT* (target-biased sampling, artificial potential field, and dynamic step-size informed rapidly-exploring random tree star) algorithm to solve the collision-free 3D path-planning problem for a 6-DOF apple-harvesting robotic arm. To improve computational speed and search directionality, the method integrates target-biased sampling and a distance-regulated artificial potential field (APF) into the Informed-RRT* framework. Furthermore, an obstacle-distance-based dynamic step-size mechanism is introduced to optimize spatial exploration. The generated routes undergo greedy path pruning and cubic B-spline smoothing to ensure kinematic executability. The simulation results in complicated ROS-based scenarios demonstrate that the TAD-IRRT* algorithm achieves a 100% planning success rate, reducing the average computational time and joint-space path length by approximately 60.1% and 15.6%, respectively, compared to the standard Informed-RRT*. Kinematic analysis via Fourier curve fitting ($R^2=0.9849$) confirms continuous angular velocity and acceleration without high-frequency chattering. Physical prototype experiments in the dense-obstacle scenarios show that the proposed method increases the path execution success rate by 36.7% and reduces the average execution time by 41% compared to the standard Informed-RRT* algorithm. The proposed approach effectively balances high-quality path generation with low computational overhead, providing a reliable and safe solution that significantly reduces mechanical wear. Full article

With the advancement of aerospace technology, full-scale wind tunnel testing has become a crucial approach to overcoming bottlenecks in hypersonic technology. The design of ultra-large, high-performance nozzles stands out as one of the core challenges. This paper focuses on a profiling design method for supersonic/hypersonic nozzles with interchangeable throats at the 6 m outlet scale, addressing issues such as significant boundary layer effects and difficulties in achieving variable Mach numbers due to the large dimensions. An empirical boundary layer correction method is proposed to efficiently compensate for viscous effects. By parameterizing and controlling the Mach number distribution along the nozzle axis using cubic B-spline curves and applying the method of characteristics for accurate inviscid supersonic flow field computation, the nozzle profile is optimized. To enable multi-Mach-number operation, a design strategy is adopted, where the high-Mach-number profile serves as the baseline, and the low-Mach-number throat section is inversely designed to ensure a smooth transition between multi-Mach nozzles and a shared expansion section. Using this approach, nozzle profiles for Mach numbers 4, 5, and 6 were successfully designed and validated through fully viscous CFD simulations. Results demonstrate that under all design conditions, a wide and uniform core flow region forms at the nozzle exit, with no strong shock waves present in the flow field. This study confirms the effectiveness and reliability of the integrated design method for large-scale interchangeable-throat nozzles, providing important theoretical foundation and technical support for the future development of advanced large-scale hypersonic wind tunnels. Full article

Insulation failure in aviation generator windings is one of the most common faults. Modern aircraft winding materials often employ polyimide enameled wire, making research on its reliability and health monitoring particularly important. Based on the relationship between temperature and aging rate described by the Arrhenius law, this study designed accelerated thermal aging experiments, testing twisted-pair, coil, and winding samples made of copper-core polyimide enameled wire. The variation in multiple parameters was visualized using B-spline fitting, ultimately identifying parallel equivalent capacitance as the most suitable parameter for monitoring generator winding insulation. It was also indicated that aging of the winding insulation coating has almost no effect on the performance of the electrical system. Finally, experimental data were processed using Bayesian nonlinear regression, where prior data were updated with new data to obtain posterior aging curves. When the IC ($C_p$) value reaches 1.2009 and 1.4089 times its initial value, the sample is considered to have reached 50% and 100% of its lifespan, respectively. This provides a reference approach and quantitative indicators for predicting the lifespan of polyimide enameled wire windings. Full article

We present a hybrid algorithm for 3D obstacle-avoidance path planning of a six-axis robotic arm in cable inspection environments. It improves on traditional RRT, which suffers from blind sampling and low efficiency, and APF, which tends to become stuck in local optima and has unstable potential fields. For the bidirectional RRT, we introduce target-biased sampling and a dynamic step-size expansion strategy driven by target attraction to enhance sampling directionality. For the APF, we optimize the potential field function by incorporating shape and size factors, use simulated annealing to overcome local optima, and apply Gaussian filtering to smooth the potential field. A triangular inequality pruning strategy with a target chain is then used to optimize the initial path, combined with cubic B-spline curves for path smoothing, and we design a simplified collision detection method to reduce computational cost. Simulation experiments are carried out in 2D and 3D spaces, as well as in a robotic arm setup that mimics cable inspection. Compared with basic RRT, bidirectional RRT, and the RRT-APF fusion algorithm, our method achieves significant improvements in average iteration count, planning time, path length, and number of generated nodes. The resulting trajectories are shorter and smoother, effectively boosting the efficiency and quality of 3D obstacle-avoidance path planning for six-axis robotic arms, and offering a practical solution for engineering scenarios such as power line inspection. Full article

Background: Current guidelines recommend lobectomy for tumors > 20 mm on CT, yet systematic CT–pathology size discordance may contribute to size-threshold–driven surgical decisions. We hypothesized that CT-based tumor diameter differs from pathological size near the 20 mm surgical boundary, potentially leading a proportion of patients to undergo more extensive resection than pathology would indicate under a size-only rule. Methods: We retrospectively analyzed 1096 patients undergoing thoracoscopic surgery for clinical stage I non-small cell lung cancer at a single center (2020–2024). CT–pathology agreement was assessed via Bland–Altman analysis. Optimal CT cut-off was identified using restricted cubic spline (RCS) modeling, internally validated with bootstrap resampling (B = 2000), and evaluated by decision curve analysis (DCA). Results: CT showed size-dependent bias: overestimation in small tumors (T1a: +4.21 mm) transitioning to underestimation in larger lesions (≥T2: −7.49 mm). At the 20 mm threshold, 15.8% of patients (n = 173) underwent lobectomy despite pathological size ≤ 20 mm (potential overtreatment). RCS modeling and bootstrap-optimized DCA identified 23 mm as the candidate revised threshold. Adopting CT > 23 mm would reclassify 108 patients from lobectomy to sublobar resection, reducing size-threshold–defined potential overtreatment by 51.4% while maintaining sensitivity for true ≥ T2 tumors. Conclusions: CT demonstrates size-dependent discordance with pathological size; this discordance likely reflects both CT measurement inaccuracy and specimen shrinkage after fixation, and the relative contributions cannot be separated from these data. A candidate 23 mm CT threshold, supported by DCA and internal bootstrap validation, could reduce size-threshold–defined potential overtreatment by 51% in this cohort. Prospective multicenter validation is required before clinical implementation. Full article

In computer-aided geometric design (CAGD), the Bernstein basis was extended to the B-spline basis through knot vectors and recursive construction, shifting from a global polynomial form to a locally supported piecewise representation. The Ball basis, composed of quadratic and cubic polynomials, is similar to the Bernstein basis of degree 3. This paper proposes a generalization for a spline-type and creates a piecewise polynomial extension, called the Ball-Spline basis, consisting of symmetric polynomial segments of degrees 2, 3, 3, and 2, arranged in a symmetric structure with the highest continuity order—$C^1$ continuity between the quadratic and cubic segments, and $C^2$ continuity between the two cubic segments. The cubic basis is constructed by multi-order spline technology and generated to higher degrees by an integral method. Compared with the B-spline basis, the proposed Ball-Spline basis shares its fundamental properties, such as positivity, normality, and local support, and generates design curves with fewer control points under the same approximation accuracy in certain examples. Thecurves generated by the Ball-Spline basis functions exhibit numerical stability under knot perturbations and admit interpretable geometric and physical properties. Full article

In ultrasonic nondestructive testing, maintaining the ultrasonic sensor in normal contact with curved surfaces is pivotal for acquiring valid defect signals. Replacing manual operation with a robotic arm ensures stable signal collection, while stable and fast trajectory planning for complex curved-surface tracking remains a key challenge. This research investigates gesture-driven robotic trajectory planning and impact optimization via the particle swarm optimization (PSO) algorithm in the robot joint space for rapid and smooth movement. Gesture trajectories are acquired via a Leap Motion device, with unified mapping established through spatial transformations among gesture, simulation, and experimental robot spaces. PSO is utilized to optimize trajectories, enhancing accuracy and controllability. Median filtering is applied to trajectory coordinate data to suppress errors from hand tremor and sensor limitations, followed by introducing a surface normal offset to generate pose matrices at each trajectory point. Systematic comparison of interpolation methods (polynomial, cubic spline, circular, cubic B-spline) reveals that cubic B-spline interpolation achieves the shortest execution time under angular acceleration constraints. The results show that PSO optimizes point-to-point trajectories based on 5-5-5 polynomial interpolation, with impact force and execution time as objectives, yielding the optimal trajectory with minimal time under acceleration constraints. This research provides valuable methodological references for robotic manipulator trajectory planning and optimization in complex curved-surface ultrasonic testing. Full article

Induction motors constitute a major share of industrial drives, making reliable fault detection essential for maintaining operational continuity. This work develops a Bayesian classifier for identifying rotor-bar damage using start-up current measurements represented in the frequency domain. The spectra are modelled as smooth functional curves using a hierarchical B-spline formulation, and posterior sampling provides a generative mechanism for augmenting scarce labelled data. Classification is performed using a Bayesian Gaussian mixture model, where each prediction is obtained by averaging over thousands of posterior samples, yielding stable and interpretable probability estimates. In experimental evaluation, the proposed approach achieves consistent separation between healthy and faulty motors across repeated training runs, correctly identifying all test cases in the binary classification setting and exhibiting more stable probability estimates than logistic and soft-max regression under limited labelled data. The model additionally signals atypical responses for unmodelled faults, indicating potential for anomaly detection. These findings highlight the suitability of Bayesian functional modelling as a reliable tool for induction motor condition monitoring. Full article

Functional data analysis (FDA) provides a framework for representing high-frequency or longitudinal observations as smooth functions, enabling principled dimension reduction and feature extraction. We develop a B-spline-based FDA approach with a total variation penalty to model daily PM₁₀ trajectories, with smoothing parameters selected via AIC and BIC. Functional principal component analysis (FPCA) is applied to identify dominant temporal patterns, including overall levels, seasonal deviations, and episodic peaks, while preserving abrupt changes. This methodology allows for flexible and interpretable summaries of complex time series and comparisons across spatial or temporal domains. We apply this framework to 365-day PM₁₀ curves from 28 monitoring stations in Chungcheongbuk-do, Korea, for 2022. The first four principal components capture over 80% of total variation, reflecting winter peaks, early spring fluctuations, and summer troughs. Urban–rural contrasts examined via functional two-sample t-tests and FPCA scores reveal minimal differences at the functional level. This study illustrates how FDA, combined with penalized B-splines, can concisely summarize complex temporal dynamics, quantify dominant patterns, and offer a flexible framework for analyzing environmental time series and other functional datasets. The approach provides a general strategy for understanding temporally structured processes in various scientific fields. Full article

Non-uniform rational B-spline (NURBS) surfaces are effective for accurately modeling curved geometries, and research in this area has recently increased. In this study, point cloud data obtained from two challenging test environments (a convex wooden object and the widely used Stanford Bunny dataset from the literature) were used to predict the u and v parameter values corresponding to positions in the knot vectors, to determine the knot points of NURBS surfaces. The u and v parameters were predicted with accuracies of 92.60% and 93.20% for the wooden object, and 85.50% and 84.40% for the Stanford Bunny. The models’ decision-making processes were analyzed using explainable artificial intelligence (XAI) methods, including SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME). Predicted knot points were compared with the calculated knot points, which are considered as actual, yielding root mean square errors (RMSE) of 0.09 mm for the wooden object and 0.02 mm for the Stanford Bunny. This study fills a gap in the literature by predicting knot points and providing XAI-based analyses, demonstrating that the approach effectively preserves the characteristic features of NURBS surfaces across different geometries. Full article

To address the limitations of traditional analytical modeling in capturing complex surface topographies, this paper presents comprehensive research on the error sensitivity mechanism, loaded tooth contact analysis (LTCA), and load-bearing contact characteristics of curved face gears based on high-precision point cloud modeling. The primary objectives are threefold: (1) to establish a high-fidelity topological reconstruction framework using Non-Uniform Rational B-Splines (NURBS) to bridge the gap between discrete data and finite element analysis (FEA); (2) to reveal the inherent mechanical response and sensitivity mechanism to spatial installation misalignments; and (3) to evaluate the contact performance and transmission error fluctuations under operational loads. Specifically, an analytical discretization method is proposed for point cloud generation, followed by a dual-path validation system integrating “rigid tooth contact analysis (TCA)” and “loaded FEA”. The results demonstrate that the proposed reconstruction achieves a superior accuracy with a Root Mean Square Error (RMSE) of 2.2 × 10⁻³ mm. Furthermore, shaft angle error is identified as the dominant sensitivity factor affecting transmission smoothness and edge contact, exerting a more significant influence than offset and axial errors. Compared with existing research on arc-tooth and helical face gears, this work provides a more robust closed-loop verification for curved profiles, revealing that material elastic deformation increases transmission error amplitude by 10.1% to 17.2%. These insights offer a theoretical reference for the high-precision assembly and tolerance allocation of helicopter transmission systems. Full article

The windings of aerospace motors are fabricated using enameled wires; with polyimide (PI) serving as the primary material for their insulating enamel coatings, thermal aging is the predominant factor contributing to insulation failure in enameled wires. The prolonged natural aging process of enameled wires, coupled with the complexity and sluggish variation rates of dielectric parameters used for aging monitoring, presents significant challenges in developing a universal method for assessing insulation performance. To address this challenge, our study determined accelerated aging conditions based on the Arrhenius law, fabricated twisted-pair specimens, and implemented a step-stress aging protocol, in order to monitor the insulation capacitance (IC) and dielectric dissipation factor (tan δ) of the sample. Finally, a two-parameter Weibull distribution plot was established to characterize the relationship between service life and failure probability. Initial-value normalization combined with B-spline interpolation was employed to construct IC–life correlation curves. A novel method for monitoring PI-enameled wire insulation life using IC variation rate was proposed and experimentally validated, providing a methodological framework for lifespan prediction of aerospace motor windings. Finally, a two-parameter Weibull distribution plot was established to characterize the relationship between service life and failure probability. Initial-value normalization combined with B-spline interpolation was employed to construct IC–life correlation curves. The rationality of the method using IC change rate to monitor the insulation lifetime of polyimide-enameled wire was verified, the lifetime assessment of aviation motor stator windings was achieved by monitoring corresponding dielectric parameters, and a reference standard for the maintenance and support of aviation equipment was provided. Full article

In Building Information Modeling (BIM) of bridge piers, persistent limitations have been observed in the modeling of spiral hoop rebar with variable pitch and diameter. Taking Revit as an example, its built-in family files can only generate spirals with constant geometry. When dealing with non-uniform rebar, designers often have to rely on segmented modeling or manual operations, which is not only time-consuming but also prone to deviations. To solve this problem, this paper proposes a parameterized modeling method based on the secondary development of Revit. By combining the Revit API with the C# programming language, the spiral equation is embedded into the Non-Uniform Rational B-Spline (NURBS) curve reconstruction framework, realizing the continuous modeling of spiral hoop rebar in a unified model. This method also allows users to flexibly input parameters such as cover thickness, rebar diameter, and segment length through a graphical user interface. Through comparative experiments, the proposed method and the traditional family file modeling method were verified respectively in the modeling of a single column and an entire bridge pier. The results indicate that the proposed method reduces the average modeling time of a single bridge pier by 66.5% and that of the entire project by 48.7%. While maintaining high geometric accuracy, this method significantly shortens modeling time and reduces workload, especially demonstrating higher consistency in pitch transition sections and conical sections. Beyond technical performance, this study also demonstrates that the secondary development of Revit provides a practical and feasible solution for the efficient, precise, and generalizable modeling of complex reinforcing bar components in terms of expanding BIM functions, which holds significant practical implications. Full article

Short dry spells during the rainy season have become increasingly common in Brazil, reinforcing the need for soil water conservation practices. Plastic mulching can enhance plant water use and mitigate abiotic stress. This study evaluates water use efficiency in terms of soil physical quality, root systems, and photosynthetic performance of citrus plants grown in different Inceptisols. The field experiment, in a randomized block design with a split-plot arrangement, was conducted in Lavras, Brazil, and involved citrus (orange) plants from 2012 to 2014. Undisturbed soil samples were collected at depths of 0.00–0.05, 0.20–0.25, and 0.90–0.95 m, two years after the installation of white plastic (WP), black plastic (BP), and no plastic (NP) mulching treatments in two Inceptisol types, totaling 54 samples. The soil water-retention curve, pore size distribution, and soil physical quality indicators were determined, and root system distribution maps were generated using B-splines. Leaf gas exchange was measured under contrasting precipitation conditions. Inceptisol I showed minimal impact from mulching, except for the bulk density and total porosity, which positively correlated with transpiration under BP. In contrast, in Inceptisol II, WP increased photosynthetic rates under low- and high-precipitation conditions but reduced water use efficiency, correlating positively with macropores and negatively with micropores. Plastic mulching reduces physiological stress in citrus and improves soil physical quality, with WP being the most effective across precipitation levels, particularly in less stable soils. Full article

This study presents an efficient numerical scheme for solving the generalized nonlinear time-fractional Klein–Gordon equation. The Caputo time-fractional derivative is discretized using a conventional finite-difference approach, while the spatial domain is approximated with uniform hyperbolic polynomial B-splines. These discretizations are coupled through the $\theta$-weighted scheme. The uniform hyperbolic polynomial B-spline framework extends classical spline theory by incorporating hyperbolic functions, thereby enhancing flexibility and smoothness in curve and surface representations—features particularly useful for problems exhibiting hyperbolic characteristics. A rigorous stability and convergence analysis of the proposed method is provided. The effectiveness of the scheme is further validated through numerical experiments on benchmark problems. The results demonstrate up to two orders of magnitude improvement in $L_{\infty }$ error norms compared to prior spline methods. This substantial accuracy enhancement highlights the robustness and efficiency of the proposed approach for fractional partial differential equations. Full article