Gear manufacturing error is one of the main sources of vibration and noise in gears; its influence on the dynamic transmission behaviour of gear systems is a research hotspot. In the current study on the effect of the manufacturing errors, the processing methods of the errors are mostly rough or hypothetical, so the analysis results cannot provide high reference value. This paper proposes a distinctive method to analyse the vibration response of helical gears in the presence of random manufacturing errors and modifications. The presented study performs tooth contact analysis (TCA) with the real tooth surface containing the random tooth profile error and the modification and performs loaded tooth contact analysis (LTCA) based on the superposition of the random pitch error and the initial gap between mating teeth obtained by TCA. Furthermore, the dynamic excitations, including time-varying mesh stiffness and meshing impact, are computed using the above-mentioned TCA and LTCA. The processing method for the manufacturing errors in this paper is reasonable and close to the actual situation of gear engagement. Using this proposed method, statistical analysis was carried out under machining accuracy grades 5, 6 and 7 to show the effect of the different distributions of random manufacturing errors on the gear vibration. The analysis results are of practical significance and provide references for the design and vibration control of gear drive systems.

In the research of gear transmission, the vibration and noise problem has received many concerns all the times. Scholars use tooth modification technique to improve the meshing state of gearings in order to reduce the vibration and noise. However, few of researchers consider the influence of measured manufacturing errors when they do the study of tooth modification. In order to investigate the efficiency of the tooth modification in the actual project, this paper proposes a dynamic model of a helical gear pair including tooth modification and measured manufacturing errors to do a deterministic analysis on the dynamical transmission performance. In this analysis, based on the measured tooth deviation, a real tooth surface (including modification and measured tooth profile error) is fitted by a bicubic B‐spline. With the tooth contact analysis (TCA) and loaded tooth contact analysis (LTCA) on the real tooth surface, the loaded transmission error, tooth surface elastic deformation, and load distribution can be determined. Based on the results, the time‐varying mesh stiffness and gear mesh impact are computed. Taking the loaded transmission error, measured cumulative pitch error, eccentricity error, time‐varying mesh stiffness, and gear mesh impact as the internal excitations, this paper establishes a 12‐degree‐of‐freedom (DOF) dynamic model of a helical gear pair and uses the Fourier series method to solve it. In two situations of low speed and high speed, the gear system dynamic response is analyzed in the time and frequency domains. In addition, an experiment is performed to validate the simulation results. The study shows that the proposed technique is useful and reliable for predicting the dynamic response of a gear system.

Due to the limitation of machining accuracy, the transmission performance uncertainty of mass gears must be evaluated quantitatively to provide the basis for its application in the whole machine. Based on the polynomial chaotic expansion (PCE) method, a dynamic uncertainty analysis method for gear systems with a specified precision was proposed in this paper. Combined with tooth surface contact analysis and load-bearing contact analysis, a dynamic model of the gear system was established to fully reflect the influence of typical manufacturing errors. Based on this, a PCE model was established to approximate the system dynamics model. The dynamic uncertainty of the gear system was quantified based on the PCE approximation model and the Monte Carlo method, respectively, and the computational accuracy and efficiency of the PCE model with different orders and numbers of sample points were compared and analyzed. Finally, Sobol′ sensitivity indices from the PCE model of the gear system to random errors were computed, and the primary and secondary relationships of influence on the dynamic performance of the gear system were determined. The results showed that the PCE method had good applicability to the quantification of dynamic uncertainty and error sensitivity analysis of gear systems, and it had both accuracy and high efficiency.

Taking a herringbone star gear transmission (HSGT) with floating sun gear as an example, the system bifurcation characteristics with the changing of the eccentric error of star gear and the working frequencies are analyzed. For this analysis, a generalized dynamic model of HSGT considering the manufacturing eccentric errors, time‐varying mesh stiffness, and load balancing mechanism is established and solved by numerical method. The floating process of sun gear is explained. In this paper, there are seven cases about the eccentric errors of star gears which are calculated, respectively. To study the effect of the working frequencies (including meshing frequency and rotation frequency), the calculation is done at three kinds of input speed in which the working frequencies are close to the system natural frequencies. The results are demonstrated in detail by the bifurcation diagrams, phase plane plots, and Poincare maps. The system bifurcation characteristics are particularly analyzed and compared in every case. This work provides important guidance to the engineering of HSGT.

The foaming process of asphalt is a complex multiphase flow mixing and heat transfer behavior. Analyzing this behavior from a macroscopic perspective often overlooks the details of multiphase flow, while microscopic analysis overly focuses on theoretical studies at the molecular level and neglects the overall characteristics of multiphase flow. Therefore, this paper adopts the lattice Boltzmann method at the mesoscopic scale to analyze the asphalt foaming behavior. Taking the asphalt foaming chamber as the research object and using the average pressure and average flow velocity of the chamber as evaluation indicators, a numerical simulation analysis of the asphalt foaming behavior inside the chamber is conducted, with comparative verification through asphalt foaming experiments. The study explores the influence of structural parameters on the average pressure and average flow velocity of the chamber, and analyzes how different structural parameters of the chamber affect the asphalt foaming behavior. The results show that within a certain range, the smaller the inlet and outlet sizes, the greater the outlet pressure and velocity of the chamber. This leads to more sufficient heat exchange between hot asphalt and water inside the chamber, thereby increasing the expansion rate and half-life of the foamed asphalt. The volume of the chamber has a significant impact on its average pressure; increasing the chamber volume can promote heat exchange between hot asphalt and water, thus enhancing the expansion rate of the foamed asphalt.