Zhi Chen

Binocular camera calibration is the core foundation of 3D vision technology, and its performance directly determines the accuracy of subsequent tasks. Zhang’s checkerboard method relies on calibration targets and suffers from poor scene adaptability, whereas conventional Kruppa self-calibration is prone to parameter divergence, low accuracy, and slow convergence. To address these issues, this paper proposes a boardless stepwise self-calibration method for binocular cameras based on an improved Kruppa equation. The method introduces (1) a stepwise decoupled optimization strategy that alternates between intrinsic and distortion parameters, combined with a SIFT + bidirectional FLANN + RANSAC + Census feature pipeline; (2) a multi-constraint regularization framework that enforces focal-length consistency, principal-point bounds, and a distortion penalty; and (3) an entropy-based feature-coverage criterion with inheritance-based batch tuning for streaming production-line images. Experiments on 800 binocular pairs from a laboratory-simulated pin-shaft production line show that the proposed method achieves an average reprojection error of 0.52 px, an 83.6% reduction over the traditional Kruppa method, approaching Zhang’s calibration. The stepwise solver converges within 7.4 inner iterations per batch, versus 23.31 iterations for the Kruppa baseline. In an end-to-end pin-shaft length measurement task, the mean absolute error is 3.01 mm, on par with Zhang’s calibration and well within the ±5 mm industrial tolerance; even under strong vibration-blur interference, the error remains 3.32 mm.

The structure of coal shearer drums significantly influences the transportation efficiency and load fluctuations of thin seam coal shearers. To enhance drum efficiency and reliability, this paper proposes a collaborative optimization method based on an improved NSGA-II algorithm. Initially, using the Discrete Element Method (DEM), we analyze the impact of helical blades on transportation performance and investigate novel designs for two types of coal-guiding drums. To optimize dynamic performance, concepts like spatial density and adaptive radius are introduced, proposing an NSGA-II enhancement strategy based on spatial density for the collaborative optimization of drum structure and motion parameters. Finally, the entropy-weighted TOPSIS method is used for subjective evaluation to select the optimal solution. Research findings demonstrate that this collaborative optimization method significantly enhances drum reliability, reducing load fluctuations by 46.34%, increasing transportation efficiency by 7.06%, and decreasing transportation power by 27.31%.

Residual stress induced by solution treatment in 6061 aluminum alloy can lead to workpiece deformation, or even premature failure. The efficiency of traditional heat treatment for relieving residual stress is relatively low. Therefore, this study introduces a novel cryogenic treatment technique to reduce residual stress. The optimal cryogenic process parameters were achieved by orthogonal experiments: cryogenic temperature of 113 K, holding time of 24 h, 1 cryogenic cycle, and a cooling rate of 3 K·min⁻¹, and the residual stress of aluminum alloy was measured by the blind hole method. The microstructural evolutions in 6061 aluminum alloy were tested by OM, SEM, and TEM. The results show that the introduction of cryogenic treatment can reduce residual stress in 6061 aluminum alloy by 64%, mainly due to the reduction of dislocations and the uniform distribution of β’’ phase.

Cemented carbide is often used as the pick-tip material for conical picks. The pick-tip often experiences premature failure due to insufficient toughness. This paper aims to improve the impact toughness of cemented carbide through electromagnetic coupled cryogenic treatment. A theoretical model between process parameters and impact toughness is established. The optimal parameters are determined as follows: a cryogenic temperature of −190 °C, cryogenic time of 24 h, magnetization intensity of 1.5 T, and magnetization time of 15 s. The treatment improves the impact toughness by 11.39% compared with the heat treatment. Microstructure analysis indicates a notable increase in dislocations and grain refinement within the Co phase, attributing to the enhanced toughness.

The machining residual stress produced in the cutting process of aluminum alloy parts can easily lead to a scrap of the processed parts. In order to reduce the residual stress of aluminum alloy in the milling process, based on the Taguchi-Grey relational approach, the effects of different milling parameters on the residual stress and surface roughness of 2A12 aluminum alloy were studied. To reduce the residual stress and surface roughness of 2A12 aluminum alloy, optimized milling parameters were obtained. To further reduce the milling residual stress of 2A12 aluminum alloy, the samples processed by the optimized milling parameters were treated by cryogenic treatment and artificial aging. The residual stress of the sample was measured by the blind hole drilling method, and the evolution mechanism of the microstructure to reduce the machining residual stress was revealed. The results show that the combination of deep cooling treatment and oil bath aging can effectively reduce the residual stress on the machined surface of the aluminum alloy and facilitate a more uniform distribution of the residual stress inside the specimen. The effect of the coarse second phase on the residual stress in the microstructure is not significant, and the fine and diffusely distributed precipitation phase is beneficial to the reduction of the residual stress in the aluminum alloy.

The working load on automotive components is continuously rising, and the mechanical performance requirements for component materials are rising along with the growth trend toward light weight and high dependability in automobiles. In this study, the response characteristics of 51CrV4 spring steel were taken to be its hardness, wear resistance, tensile strength, and impact toughness. Prior to tempering, cryogenic treatment was introduced. Through the Taguchi method and gray relational analysis, the ideal process parameters were discovered. The ideal process variables were the following: a cooling rate of 1 °C/min, a cryogenic temperature of −196 °C, a holding time of 24 h, and a cycle number of three. An analysis of variance revealed that the holding time had the greatest effect on the material properties, with an effect of 49.01%. The yield limit of 51CrV4 was increased by 14.95% and the tensile strength was increased by 15.39% with this group of processes, and the wear mass loss was reduced by 43.32%. The mechanical qualities had a thorough upgrade. Microscopic analysis revealed that cryogenic treatment resulted in refinement of the martensite structure and significant differences in orientation. Additionally, bainite precipitation occurred, exhibiting a fine needle-like distribution, which positively influenced impact toughness. Analysis of the impact fracture surface showed that cryogenic treatment led to an increase in dimple diameter and depth. Further analysis of the elements revealed that calcium (Ca) weakened the negative effect of sulfur (S) on 51CrV4 spring steel. The overall improvement in material properties provides guidance for practical production applications.

Aiming at the multiobjective topology optimization design of the structure, this paper proposes a method to establish the comprehensive objective function based on the normalized subobjective of the compromise programming method and to determine the weight coefficient of the subobjective of the comprehensive objective function by the analytic hierarchy process (AHP). By using statistical analysis and modal analysis, the static and dynamic characteristics of the gear can be obtained. The single objective topology optimization is used to reduce the compliance of the gear and elevate the low-order natural frequency, and the frequency weighting method is used to suppress the oscillation phenomenon in the frequency-single-objective optimization. AHP was used to determine the weight coefficient of each subtarget. The compromise programming method is used for multiobjective topology optimization, and the gear design is improved according to the optimization results. By analyzing the improved gear structure, the weight of the optimized gear is reduced by 25.3%. The overall stiffness performance and strength performance are enhanced, and the natural frequencies of each order are improved to different degrees.