Gears are usually measured by the contact metrology method in gear measuring centers or coordinate measuring machines. Recently, three-dimensional (3D) optical scanning, a non-contact metrology method, has been applied in the industry as an advanced measurement technology mainly due to its high efficiency. However, its applications to gears with complicated geometry, such as face gears, are still limited due to its relatively low accuracy and the void of related measurement solutions. In this work, an accurate measurement solution with 3D optical scanning is proposed for the tooth surface deviations of orthogonal face gears. First, point cloud collection is carried out by the 3D scanner. Furthermore, the measurement solution is implemented with a three-stage algorithm by aligning point clouds with the design model. Subsequently, 3D modeling is studied by numbering the points and reconstructing the real tooth surfaces. An example with a measurement experiment and loaded tooth contact analysis is given to show the validity of the proposed method.

Ultrasonic vibration-assisted cutting (UVC) is progressively being used in machining as it can significantly promote the fabrication process. However, the ultrasonic vibration affecting the cutting process is still controversial. The full-transient cutting process is proposed in this study to analyze the affecting mechanism induced by ultrasonic vibration in the cutting process. This novel model is the first developed based on the fact that ultrasonic vibration would change mechanical behaviors and the cutting process. For example, the reduction of shear flowing stress in the primary shear zone and alteration of the shear angle in the UVC process. Then, considering those coupled effects, a novel model is proposed to determine the average and transient cutting forces. Here, insight and understanding into the physical phenomenon in UVC are provided. The effectiveness of the proposed model is verified by comparison with experimental results and analytical models available in the literature, with cutting parameters varying from macro to micro-scale. The results show that the ultrasonic vibration affects the cutting process in a complicated way, which is determined by transient characteristics, acoustic softening, thermal softening, plowing, and friction. Those effects on cutting performances in the UVC process under various cutting scenarios are investigated and discussed systematically. The average deviation of cutting forces between experiments and values predicted by the proposed model for Ti6Al4V, AISI 1045, and Al6063 is about 7%, 10.2%, and 11%, respectively. The deviation decreases with the increase of cutting speed in the machining of Ti6Al4V, which is different from the machining of other materials. This is contributed by the varied effect of ultrasonic vibration on the cutting process.

Optimization with edge contact avoidance and contact stress minimization is essential for gear design. Due to the complex geometry of modified helical face gear drives, it is complicated to find the optimal design parameters with the consideration of issues including loading, assembly errors, and edge contact. As the finite element method is tedious and time-consuming, an optimization model with a simplified algorithm of the loaded tooth contact analysis with errors (ELTCA) for modified helical face gears is presented, and it can programmatically optimize the contact stress with edge contact avoidance. Firstly, a simplified ETCA algorithm is introduced, which reduces the five unknowns in the traditional contact equations to three. Secondly, the LTCA is analytically implemented according to the Hertz theory. Subsequently, an optimization model with the objective function of avoiding edge contact and reducing maximum contact stress is proposed. Furthermore, the proposed model is applied to reveal the effects of design parameters and assembly errors on the optimized contact path and stress. The results show that the optimization model is accurate and efficient; the design parameters and assembly errors have great effects on the meshing of modified helical face gears.

Tin-based gas sensors have been developed for many years owing to their advantages of low price, high response and stability. However, selectivity remains a significant issue. Herein, Ag-SnO₂ nanofibers are synthesized using AgCl as the doping reagent. The 3%Ag-SnO₂ nanofibers sensors show a high response of 68 toward 1 ppm H₂S at 90 °C. Besides, the sensor with 3% AgCl possesses the shortest response time about 136 s at 150 °C which is only 30% value of the sensor without AgCl doping. It is also demonstrated that the nanofibers show a high selectivity towards H₂S. According to the ex situ x-ray photoelectron spectrum and x-ray diffraction results, AgCl was transferred to Ag₂S after Ag-SnO₂ was exposed to H₂S, and reversible transformation between Ag₂SO₄ and Ag₂S was the main mechanism for H₂S detection. Compared with pure SnO₂ nanofiber sensors, the presence of Ag₂S with high conductivity greatly affects the resistance to H₂S, resulting in high selectivity and response. This mechanism differs from that of the transformation between Ag₂O and Ag₂SO₄. This study may provide a new strategy for the design and investigation of sensors with high selectivity.