Laser quenching is one of the most outstanding gear tooth surface quenching methods due to its high efficiency, environmental friendliness, and performance consistency. Since gear tooth surface laser quenching requires repeated scanning, changing the laser scanning velocity and power by program control can meet the needs of variable depth quenching. The effects of laser scanning velocity and output power on the quenching depth and surface Rockwell hardness after quenching were studied and experimentally analyzed. The result shows that by adjusting the parameters, the surface hardness of the specimen changes slightly with the actual received laser energy. However, the quenching depth can be consistent with the laser scanning velocity. The maximum surface Rockwell hardness that a laser quenched material can achieve depends on the material itself, not on the laser power or scanning velocity. Compared with accelerated laser quenching, decelerated laser quenching is more suitable for tooth surface machining due to the cumulative effect of energy within the quenching depth range of metal materials.

Purpose Considering the time-varying pressure angle and dynamic clearance, the effects of rotational speed, tooth surface friction, and tooth surface morphology on the system’s dynamic response are studied. Method An improved gear nonlinear model is proposed, which considered nonlinear factors such as time-varying pressure angle, position angle, tooth surface morphology, and tooth surface friction. The time-varying dynamic backlash is deduced, and the nonlinear dynamic equation of the gear is established. The nonlinear dynamic response of the gear system is obtained based on Runge–Kutta method. Results The influence of the rotational speed and tooth surface friction on single-stage spur gear system response is analyzed through the analysis of the bifurcation diagram, the three-dimensional spectrum diagram, the proportion of the meshing state, and the largest dynamic meshing force (LDMF). Dynamic response differences between the three different model are compared. In addition, by changing the tooth surface roughness and fractal dimension, the influence of tooth surface morphology on the dynamic response of the system is studied. Conclusion Compared with the traditional model, when the dynamic center distance and dynamic pressure angle are considered, the system response may enter a chaotic state earlier. When the tooth surface friction is further considered, the chaotic state of the system response is suppressed. At the same time, the velocity of the dynamic transmission error is significantly reduced, and the fluctuation amplitude of the dynamic pressure angle is increased. The value of LDMF rose overall. The stability of the system response decreases with the increase of tooth surface roughness and fractal dimension. Compared with the fractal dimension, the tooth surface roughness has a more obvious effect on the dynamic response of the system.

Bevel gears are widely used in aerospace transmission systems as well as modern mechanical equipment. In order to meet the needs and development of aerospace, high-speed dynamic vehicles, and various defense special equipment, higher and higher requirements are made for the high precision and stability of gear transmission systems, as well as the prediction and control of noise and vibration. Considering the nonlinear factors such as comprehensive gear error and tooth side clearance, a dynamic model of the three-stage gear transmission system is established. The relevant physical parameters, geometric parameters, and load parameters in the gear system are considered random variables to obtain the stochastic vibration model. When the random part of the random parameters is much smaller than the deterministic part, the vibration differential equation is expanded into a first-order term at the mean of the random parameter vector according to the Taylor series expansion theorem, and the ordering equation is solved numerically. Based on the improved stochastic regression method, the nonlinear dynamic response analysis of the three-stage gear train is carried out. This results in a relatively stable system when the dimensionless excitation frequency is in the range of 0.716 to 0.86 and the magnitude of the dimensionless integral meshing error is < 1.089.