Optical interferometry is a powerful tool for measuring and characterizing areal surface topography in precision manufacturing. A variety of instruments based on optical interferometry have been developed to meet the measurement needs in various applications, but the existing techniques are simply not enough to meet the ever-increasing requirements in terms of accuracy, speed, robustness, and dynamic range, especially in on-line or on-machine conditions. This paper provides an in-depth perspective of surface topography reconstruction for optical interferometric measurements. Principles, configurations, and applications of typical optical interferometers with different capabilities and limitations are presented. Theoretical background and recent advances of fringe analysis algorithms, including coherence peak sensing and phase-shifting algorithm, are summarized. The new developments in measurement accuracy and repeatability, noise resistance, self-calibration ability, and computational efficiency are discussed. This paper also presents the new challenges that optical interferometry techniques are facing in surface topography measurement. To address these challenges, advanced techniques in image stitching, on-machine measurement, intelligent sampling, parallel computing, and deep learning are explored to improve the functional performance of optical interferometry in future manufacturing metrology.

Passive variable stiffness joints have unique advantages over active variable stiffness joints and are currently eliciting increased attention. Existing passive variable stiffness joints rely mainly on sensors and special control algorithms, resulting in a bandwidth-limited response speed of the joint. We propose a new passive power-source-free stiffness-self-adjustable mechanism that can be used as the elbow joint of a robot arm. The new mechanism does not require special stiffness regulating motors or sensors and can realize large-range self-adaptive adjustment of stiffness in a purely mechanical manner. The variable stiffness mechanism can automatically adjust joint stiffness in accordance with the magnitude of the payload, and this adjustment is a successful imitation of the stiffness adjustment characteristics of the human elbow. The response speed is high because sensors and control algorithms are not needed. The variable stiffness principle is explained, and the design of the variable stiffness mechanism is analyzed. A prototype is fabricated, and the associated hardware is set up to validate the analytical stiffness model and design experimentally.

A novel hybrid perfusion manipulator (HPM) with five degrees of freedom (DOFs) is introduced by combining the 5PUS-PRPU (P, R, U, and S represent prismatic, revolute, universal, and spherical joint, respectively) parallel mechanism with the 5PRR reconfigurable base to enhance the perfusion efficiency of the large-scale spherical honeycomb thermal protection layer. This study mainly presents the dimensional synthesis of the proposed HPM. First, the inverse kinematics, including the analytic expression of the rotation angles of the U joint in the PUS limb, is obtained, and mobility analysis is conducted based on screw theory. The Jacobian matrix of 5PUS-PRPU is also determined with screw theory and used for the establishment of the objective function. Second, a global and comprehensive objective function (GCOF) is proposed to represent the Jacobian matrix’s condition number. With the genetic algorithm, dimensional synthesis is conducted by minimizing GCOF subject to the given variable constraints. The values of the designed variables corresponding to different configurations of the reconfigurable base are then obtained. Lastly, the optimal structure parameters of the proposed 5-DOF HPM are determined. Results show that the HPM with the optimized parameters has an enlarged orientation workspace, and the maximum angle of the reconfigurable base is decreased, which is conducive to improving the overall stiffness of HPM.

Fatigue failure of gear transmission is one of the key factors that restrict the performance and service life of wind turbines. One of the major concerns in gear transmission under random loading conditions is the disregard of dynamic fatigue reliability in conventional design methods. Various issues, such as overweight structure or insufficient fatigue reliability, require continuous improvements in the reliability-based design optimization (RBDO) methodology. In this work, a novel gear transmission optimization model based on dynamic fatigue reliability sensitivity is developed to predict the optimal structural parameters of a wind turbine gear transmission. In the model, the dynamic fatigue reliability of the gear transmission is evaluated based on stress–strength interference theory. Design variables are determined based on the reliability sensitivity and correlation coefficient of the initial design parameters. The optimal structural parameters with the minimum volume are identified using the genetic algorithm in consideration of the dynamic fatigue reliability constraints. Comparison of the initial and optimized structures shows that the volume decreases by 3.58% while ensuring fatigue reliability. This work provides new insights into the RBDO of transmission systems from the perspective of reliability sensitivity.

Topology optimization is a pioneer design method that can provide various candidates with high mechanical properties. However, high resolution is desired for optimum structures, but it normally leads to a computationally intractable puzzle, especially for the solid isotropic material with penalization (SIMP) method. In this study, an efficient, high-resolution topology optimization method is developed based on the super-resolution convolutional neural network (SRCNN) technique in the framework of SIMP. SRCNN involves four processes, namely, refinement, path extraction and representation, nonlinear mapping, and image reconstruction. High computational efficiency is achieved with a pooling strategy that can balance the number of finite element analyses and the output mesh in the optimization process. A combined treatment method that uses 2D SRCNN is built as another speed-up strategy to reduce the high computational cost and memory requirements for 3D topology optimization problems. Typical examples show that the high-resolution topology optimization method using SRCNN demonstrates excellent applicability and high efficiency when used for 2D and 3D problems with arbitrary boundary conditions, any design domain shape, and varied load.

Cutting quality and efficiency have always been important indicators of glass laser cutting. Laser scanning modes have two kinds, namely, the spiral and concentric circle scanning modes. These modes can achieve high-performance hole cutting of thick solar float glass using a 532-nm nanosecond laser. The mechanism of the glass laser cutting under these two different scanning modes has been described. Several experiments are conducted to explore the effect of machining parameters on cutting efficiency and quality under these two scanning modes. Results indicate that compared with the spiral scanning mode, the minimum area of edge chipping (218340 µm²) and the minimum Ra (3.01 µm) in the concentric circle scanning mode are reduced by 9.4% and 16.4% respectively. Moreover, the best cutting efficiency scanning mode is 14.2% faster than that in the spiral scanning mode. The best parameter combination for the concentric circle scanning mode is as follows: Scanning speed: 2200 mm/s, number of inner circles: 6, and circle spacing: 0.05 mm. This parameter combination reduces the chipping area and sidewall surface roughness by 8.8% and 9.6% respectively at the same cutting efficiency compared with the best spiral processing parameters. The range of glass processing that can be achieved in the concentric circle scanning mode is wider than that in the spiral counterpart. The analyses of surface topography, white spots, microstructures, and sidewall surface element composition are also performed. The study concluded that the concentric circle scanning mode shows evident advantages in the performance of solar float glass hole cutting.

Solar rolled glass, with one micro-structure surface and another roughness surface, can cause diffuse refraction of the focused laser spot, and this phenomenon restricts the application of laser manufacturing. In this study, laser cutting of solar rolled glass with a thickness of 2.5 mm was successfully achieved with the help of dimethicone to ensure laser focusing. Dimethicone was coated on the top surface of the rolled glass processing zone, and a Z bottom–up multilayer increment with the X–Y spiral line was applied to control the cutting path. Different viscosity values of dimethicone were considered. Results showed that surface quality increased as the viscosity increased until a certain threshold was reached; afterward, the surface quality decreased or directly caused the cutting to fail. The minimum surface roughness (3.26 µm) of the processed surface (chipping: Width≤113.64 µm, area 215199 µm²) was obtained when the dimethicone viscosity and laser pulse frequency were 1000 mm²/s and 43 kHz (power 25.4 W), respectively. The micro-defects on the processed surface were few, and the edge chipping width and depth of the laser processed surface were small.

Microwave induced plasma torches find wide applications in material and chemical analysis. Investigation of a coaxial electrode microwave induced plasma (CE–MIP) torch is conducted in this study, making it available for glass surface modification and polishing. A dedicated nozzle is designed to inject secondary gases into the main plasma jet. This study details the adaptation of a characterisation process for CE–MIP technology. Microwave spectrum analysis is used to create a polar plot of the microwave energy being emitted from the coaxial electrode, where the microwave energy couples with the gas to generate the plasma jet. Optical emission spectroscopy analysis is also employed to create spatial maps of the photonic intensity distribution within the plasma jet when different additional gases are injected into it. The CE–MIP torch is experimentally tested for surface energy modification on glass where it creates a super-hydrophilic surface.

Surface accuracy directly affects the surface quality and performance of mechanical parts. Circular hole, especially spatial non-planar hole set is the typical feature and working surface of mechanical parts. Compared with traditional machining methods, additive manufacturing (AM) technology can decrease the surface accuracy errors of circular holes during fabrication. However, an accuracy error may still exist on the surface of circular holes fabricated by AM due to the influence of staircase effect. This study proposes a surface accuracy optimization approach for mechanical parts with multiple circular holes for AM based on triangular fuzzy number (TFN). First, the feature lines on the manifold mesh are extracted using the dihedral angle method and normal tensor voting to detect the circular holes. Second, the optimal AM part build orientation is determined using the genetic algorithm to optimize the surface accuracy of the circular holes by minimizing the weighted volumetric error of the part. Third, the corresponding weights of the circular holes are calculated with the TFN analytic hierarchy process in accordance with the surface accuracy requirements. Lastly, an improved adaptive slicing algorithm is utilized to reduce the entire build time while maintaining the forming surface accuracy of the circular holes using digital twins via virtual printing. The effectiveness of the proposed approach is experimentally validated using two mechanical models.

A Lagrange dynamic model is established based on small-angle approximation to improve the simulation model for shipborne helicopter landing collision. To describe fuselage motion effectively, the proposed model considers ship motion, the interaction of the tires with the deck, and tire slippage. A mechanism of sliding motion is built, and a real-time reliability analysis of the algorithm is implemented to validate the proposed model. Numerical simulations are also conducted under different operation conditions. Results show that the proposed dynamic model can simulate the collision motion of helicopter landing in real time. Several suggestions for helicopter pilot landing are likewise provided.

Crawling robots have elicited much attention in recent years due to their stable and efficient locomotion. In this work, several crawling robots are developed using two types of soft pneumatic actuators (SPAs), namely, an axial elongation SPA and a dual bending SPA. By constraining the deformation of the elastomeric chamber, the SPAs realize their prescribed motions, and the deformations subjected to pressures are characterized with numerical models. Experiments are performed for verification, and the results show good agreement. The SPAs are fabricated by casting and developed into crawling robots with 3D-printing connectors. Control schemes are presented, and crawling tests are performed. The speeds predicted by the numerical models agree well with the speeds in the experiments.

The power density of axial piston pumps can benefit greatly from increased rotational speeds. However, the maximum rotational speed of axial piston machines is limited by the cavitation phenomenon for a given volumetric displacement. This paper presents a scaling law derived from an analytical cavitation model to estimate the speed limitations for the same series of axial piston pumps. The cavitation model is experimentally verified using a high-speed axial piston pump, and the scaling law is validated with open specification data in product brochures. Results show that the speed limitation is approximately proportional to the square root of the inlet pressure and inversely proportional to the cube root of volumetric displacement. Furthermore, a characteristic constant C_p is defined based on the presented scaling law. This constant can represent the comprehensive capacity of axial piston pumps free from cavitation.

This paper presents a single-electromagnet levitation device to measure the densities and detect the internal defects of antimagnetic materials. The experimental device has an electromagnet in its lower part and a pure iron core in the upper part. When the electromagnet is activated, samples can be levitated stably in a paramagnetic solution. Compared with traditional magnetic levitation devices, the single-electromagnet levitation device is adjustable. Different currents, electromagnet shapes, and distances between the electromagnet and iron core are used in the experiment depending on the type of samples. The magnetic field formed by the electromagnet is strong. When the concentration of the MnCl₂ aqueous solution is 3 mol/L, the measuring range of the single-electromagnet levitation device ranges from 1.301 to 2.308 g/cm³. However, with the same concentration of MnCl₂ aqueous solution (3 mol/L), the measuring range of a magnetic levitation device built with permanent magnets is only from 1.15 to 1.50 g/cm³. The single-electromagnet levitation device has a large measuring range and can realize accurate density measurement and defect detection of high-density materials, such as glass and aluminum alloy.

This study aims at investigating the nonlinear dynamic behavior of rotating blade with transverse crack. A novel nonlinear rotating cracked blade model (NRCBM), which contains the spinning softening, centrifugal stiffening, Coriolis force, and crack closing effects, is developed based on continuous beam theory and strain energy release rate method. The rotating blade is considered as a cantilever beam fixed on the rigid hub with high rotating speed, and the crack is deemed to be open and close continuously in a trigonometric function way with the blade vibration. It is verified by the comparison with a finite element-based contact crack model and bilinear model that the proposed NRCBM can well capture the dynamic characteristics of the rotating blade with breathing crack. The dynamic behavior of rotating cracked blade is then investigated with NRCBM, and the nonlinear damage indicator (NDI) is introduced to characterize the nonlinearity caused by blade crack. The results show that NDI is a distinguishable indicator for the severity level estimation of the crack in rotating blade. It is found that severe crack (i.e., a closer crack position to blade root as well as larger crack depth) is expected to heavily reduce the stiffness of rotating blade and apparently result in a lower resonant frequency. Meanwhile, the super-harmonic resonances are verified to be distinguishable indicators for diagnosing the crack existence, and the third-order super-harmonic resonances can serve as an indicator for the presence of severe crack since it only distinctly appears when the crack is severe.