The traditional SIFT (Scale Invariant Feature Transform) registration algorithm is highly regarded in the field of image processing due to its scale invariance, rotation invariance, and robustness to noise. However, it faces challenges such as a large number of feature points, high computational demand, and poor real-time performance when dealing with large-scale images. A novel optimization method based on integral image technology and canny edge detection is presented in this paper, aiming to maintain the core advantages of the SIFT algorithm while reducing the complexity involved in image registration computations, enhancing the efficiency of the algorithm for real-time image processing, and better adaption to the needs of large-scale image handling. Firstly, Gaussian separation techniques were used to simplify Gaussian filtering, followed by the application of integral image techniques to accelerate the construction of the entire pyramid. Additionally, during the feature point detection phase, an innovative feature point filtering strategy was introduced by combining Canny edge detection with dilation operations alongside the traditional SIFT approach, aiming to reduce the number of feature points and thereby lessen the computational load. The method proposed in this paper takes 0.0134 s for Image type a, 0.0504 s for Image type b, and 0.0212 s for Image type c. In contrast, the traditional method takes 0.1452 s for Image type a, 0.5276 s for Image type b, and 0.2717 s for Image type c, resulting in reductions of 0.1318 s, 0.4772 s, and 0.2505 s, respectively. A series of comparative experiments showed that the time taken to construct the Gaussian pyramid using our proposed method was consistently lower than that required by the traditional method, indicating greater efficiency and stability regardless of image size or type.

This study investigates the mechanical properties of ABS parts fabricated via used deposition modeling (FDM) through integrated experimental and numerical approaches. ABS resin was used as the experimental material, and tensile tests were conducted using a universal testing machine. Finite element analysis (FEA) was performed via ANSYS 2021 to simulate stress deformation behavior, with key parameters including a gauge length of 10 mm (pre-stretching) and printing temperature gradients. The results show that the specimen exhibited a maximum tensile force of 7.3 kN, upper yield force of 3.7 kN, and lower yield force of 3.2 kN, demonstrating high strength and toughness. The non-proportional elongation reached 0.06 (6%), and the quantified enhancement multiple of AM relative to traditional manufacturing was 1.1, falling within the reasonable range for glass fiber-reinforced or specially formulated ABS. FEA results validated the experimental data, showing that the material underwent 15 mm of plastic deformation before fracture, consistent with ABS’s ductile characteristics.

In view of the problems existing in the traditional strain detection methods, such as complex operation process, inability to realize real-time measurement and great influence by the environment, the digital image correlation (DIC) method was used to measure the strain values of copper/aluminum clad plate and its components during the tensile process, and the measured results were compared with those obtained by the stretching machine and the finite element simulation measurement. The results show that the strain curves of Cu plate, Al plate and Cu/Al clad plate obtained by DIC method and tensile test are very similar. The principal strain measured by DIC method has a high consistency with that simulated by finite element method, and the surface strain distribution is basically the same as the maximum principal strain, with a maximum difference of 0.442 % and a minimum of 0.008 %. The strain differences obtained by finite element simulation has a large variation with the maximum variation of 4.950 %, while that obtained by DIC method has a small variation with the maximum variation of 0.693 %. On this basis, the precision of DIC method and finite element method was studied by introducing strain differences, which verified the feasibility and superiority of the DIC method for the tensile strain detection of Cu/Al clad plate.

As a commonly used component in robot joints, helical planetary gear system is restricted from further application in the robotics industry due to excessive maximum subsurface shear stress and vibration amplitude during their meshing motion. Tooth modification can effectively reduce the maximum subsurface shear stress and vibration amplitude of gears, making it particularly important to conduct research on the modification of helical planetary gear trains. In this study, a lumped mass method is first adopted to establish a bending-torsion-axial coupling dynamic model of the helical planetary gear train. Subsequently, multi-objective optimization modification research on the left tooth flank of the planetary gear is carried out using both traditional empirical formulas and an improved MOPSO, respectively. Then, the finite element method is employed to analyze the maximum subsurface shear stress of planetary gears under three scenarios: unmodified, traditionally modified, and modified with the improved MOPSO. Finally, the 4th-order Runge-Kutta method is used to solve the bending-torsion-axial coupling dynamic model of the helical planetary gear train system, thereby obtaining the vibration amplitude of the sun gear under the three scenarios. The research results show that the empirical formula method and the improved MOPSO reduce the maximum subsurface shear stress of the planetary gear by 12.629% and 30.107%, respectively, and decrease the vibration amplitude of the sun gear by 10.26% and 19.29%, respectively. This study provides theoretical and data support for the development of helical planetary gear modification and promotes its further application in the robotics industry.

As a commonly used component in robot joints, helical planetary gear system is restricted from further application in the robotics industry due to excessive maximum subsurface shear stress and vibration amplitude during their meshing motion. Tooth modification can effectively reduce the maximum subsurface shear stress and vibration amplitude of gears, making it particularly important to conduct research on the modification of helical planetary gear trains. In this study, a lumped mass method is first adopted to establish a bending to rsionaxial coupling dynamic model of the helical planetary gear train. Subsequently, multi-objective optimization modification research on the left tooth flank of the planetary gear is carried out using both traditional empirical formulas and an improved Multi-Objective Particle Swarm Optimization (MOPSO) algorithm featuring physics-informed search boundaries and an automated optimal selection mechanism, respectively. Then, the finite element method is employed to analyze the maximum subsurface shear stress of planetary gears under three scenarios: unmodified, traditionally modified, and modified with the improved MOPSO. Finally, the 4th-order Runge Kutta method is used to solve the bending to rsionaxial coupling dynamic model of the helical planetary gear train system, thereby obtaining the vibration amplitude of the sun gear under the three scenarios. The research results show that the empirical formula method and the improved MOPSO reduce the maximum subsurface shear stress of the planetary gear by 12.629% and 30.107%, respectively, and decrease the vibration amplitude of the sun gear by 10.26% and 19.29%, respectively. This study provides theoretical and data support for the development of helical planetary gear modification and promotes its further application in the robotics industry.