The frequency multiplication in a simplified two-cantilever system was characterized and its mass sensing capability was demonstrated. Two microcantilevers similar in cross section but different in length, with primary frequencies of 177.38 kHz [ω1 of (long) low-frequency cantilever] and 351.66 kHz [ω ₂ of (short) high-frequency cantilever], are connected micromechanically with each other by a coupling overhang. In synchronized regime, when the long cantilever is excited at its primary frequency of ω ₁ , the frequency response of the coupled short cantilever has a peak at double the primary frequency of 2 ω ₁ of the long cantilever. While in superharmonic oscillation, the drive frequency of 0.5 ω ₂ was multiplied to ω ₂ with a higher vibration power along high-frequency cantilever. Mass sensing in picogram order was demonstrated by applying polystyrene microspheres as a small mass perturbation onto the tip of low-frequency cantilever. Comparing with no mass perturbation, almost no frequency shift was observed in superharmonic oscillation although the vibration power decreased slightly, while the frequency shift was multiplied by a factor of n = 2 from 6.13 to 12.26 kHz with a slightly increased vibration power due to synchronized oscillation. A mass of 8.609 pg was then derived for the applied polystyrene microspheres, corresponding to the calculated value of 8.792 pg from geometrical size and chemical density. To the best of our knowledge, this is the first experimental demonstration of synchronized oscillation used for picogram mass sensing, as well as the original comparative study of the frequency multiplication conducted by synchronized oscillation with respect to superharmonic one.

In order to improve the image quality of the aerial optoelectronic sensor over a wide range of temperature changes, high thermal adaptability of the primary mirror as the critical components is considered. Integrated optomechanical analysis and optimization for mounting primary mirrors are carried out. The mirror surface shape error caused by uniform temperature decrease was treated as the objective function, and the fundamental frequency of the mirror assembly and the surface shape error caused by gravity parallel or vertical to the optical axis are taken as the constraints. A detailed size optimization is conducted to optimize its dimension parameters. Sensitivities of the optical system performance with respect to the size parameters are further evaluated. The configuration of the primary mirror and the flexure are obtained. The simulated optimization results show that the size parameters differently affect the optical performance and which factors are the key. The mirror surface shape error under 30 °C uniform temperature decrease effectively decreased from 26.5 nm to 11.6 nm, despite the weight of the primary mirror assembly increases by 0.3 kg. Compared to the initial design, the value of the system’s modulation transfer function (0° field angle) is improved from 0.15 to 0.21. Namely, the optical performance of the camera under thermal load has been enhanced and thermal adaptability of the primary mirror has been obviously reinforced after optimization. Based on the optimized results, a prototype of the primary mirror assembly is manufactured and assembled. A ground thermal test was conducted to verify difference in imaging quality at room and low temperature, respectively. The image quality of the camera meets the requirements of the index despite degrading.

Abrasive belt grinding is the key technology in high-end precision manufacturing field, but the working condition of abrasive particles on the surface of the belt will directly affect the quality and efficiency during processing. Aiming at the problem of the inability to monitor the wearing status of abrasive belt in real-time during the grinding process, and the challenge of time-consuming control while shutdown for detection, this paper proposes a method for predicating the wear of abrasive belt while the grinding process based on back-propagation (BP) neural network. First, experiments are carried out based on ultra-depth-of-field detection technology, and different parameter combinations are used to measure the degree of abrasive belt wear. Then the effects of different grinding speeds, different contact pressures, and different work piece materials on the abrasive belt wear rate are obtained. It can be concluded that the abrasive belt wear rate gradually increases as the grinding speed of the abrasive belt increases. With the increase of steel grade, the hardness of the steel structure increases, which intensifies the abrasive belt wear. As the contact pressure increases, the pressure on a single abrasive particle increases, which ultimately leads to increased wear. With the increase of contact pressure, the increase of the wear rate of materials with higher hardness is greater. By utilizing the artificial intelligence BP neural network method, 18 sets of experiment data are used for training BP neural network while 9 sets of data are used for verification, and the nonlinear mapping relationship between various process parameter combinations such as grinding speed, contact pressure, workpiece material, and wear rate is established to predict the wear degree of abrasive belt. Finally, the results of verification by examples show that the method proposed in this paper can fulfill the purpose of quickly and accurately predicting the degree of abrasive belt wear, which can be used for guiding the manufacturing processing, and greatly improving the processing efficiency.

In this article, a new gear generating method for the spiral bevel gear with spherical involutes tooth curves was proposed. It was analysed that the tooth flank with cone-spiral involute surface could be formed by the space trajectory of a straight line. The straight line was named as a tracing line. In the method, three motions were demanded; those were the rotary motion of the workpiece, the rectilinear motion of the end of the tracing line along the dedendum, and the rotary motion of the tracing line in the plane. The motion equations were derived. The plate milling cutter with face cutting edges could be used to machine the spiral bevel gears and the chord line of the face circle worked as the tracing line. By the method, the spiral bevel gears without principle errors whose tooth flanks are exact spherical involute curves that could be achieved.

This paper proposes a semi-cool temperature compensation algorithm based on the double exponential model of the transient temperature rise curve to improve the performance of the three-dimensional (3D) ultrasonic positioning system. The error model of 3D ultrasonic positioning system is derived and the importance of temperature to the positioning accuracy is demonstrated. Then the double exponential model of the transient temperature rise curve derived by difference principle is established through dynamic system identification method. On this basis, the semi-cool temperature compensation algorithm is proposed, which includes the estimation of the initial time t0, the principle of the choice of parameter k. The effectiveness of algorithm is verified by temperature measurement experiments. The impact of the ambient temperature on the algorithm is also analyzed qualitatively. In the end, the semi-cool temperature compensation algorithm is proved to able to improve the performance of the 3D ultrasonic positioning system by the comparison experiments respectively under static measurement of a fixed point and dynamic measurement of a fixed line.