The study of helical gear vibration and noise abroad has a history of more than 100 years. However, it was not until the 1970s that British vibration and noise expert Optiz H first systematically studied the dynamic characteristics of helical gears and spur gears, and established a set of functional expressions on the relationship between transmission error, transmission power, manufacturing accuracy and vibration and noise of helical gears. Since then, more and more experts and scholars have begun to pay close attention to the problem of helical gear vibration and noise, and no longer meet the requirements of simple formula derivation or theoretical mechanism exploration. In the 1980s, Japanese scholars such as Takao Sakai, Toshio Hideda, Yoshihiko Meizawa, etc. took the helical gear box as the research object, combined with 3D modeling, computer simulation, vibration and noise testing and other means, comprehensively and deeply studied the mechanism of helical gear vibration and noise, and achieved fruitful results. In 1993, Choy F K et al. carried out numerical simulation and experimental research on the helical gear box, studied the linear relationship between the vibration and noise of the helical gear box, introduced correlation functions to explore the nonlinear relationship between the fundamental noise frequency and harmonics, and finally summarized and developed a set of theoretical methods that can be used for the numerical prediction of the vibration and noise of the helical gear box. In 1995, Crone A developed a method to measure the strength of the structural noise source of the helical gearbox based on the enhanced vibration test of the helical gearbox of the wind turbine generator. In 2003, Tanaka summarized the prediction method from gear vibration to noise including helical gear box, which mainly includes three steps: analyzing the vibration of helical gear based on the developed program, analyzing the dynamics of helical gear using finite element method, and analyzing the sound radiation of helical gear using commercial software. This scheme can not only obtain the vibration and noise characteristics of gear and gear box, It can also master the distribution of sound pressure around the helical gear box and the distribution of noise sensitive areas in the sound field. In 2005, Hajzman M et al. summarized the vibration and noise analysis methods of common rotating systems (including gear boxes). Their newly developed model included the actual number of bearing rollers and the roller contact force acting between the journal and the housing. At the same time, they explored the relationship between the steady-state dynamic response of the entire helical gear box and the gear transmission error, and obtained the noise radiated by the housing according to the sound power. In 2010, Mohamad E N et al. developed a simulation program that can reflect the relationship between tooth profile changes and helical gear vibration and noise quality. They believed that the higher the tooth surface finish and the lower the spiral slope deviation, the lower the gear vibration excitation, the lower the noise, and the better the sound quality.
In 2020, Czako A and others discussed the relationship between static transmission error and helical gear vibration noise, and proposed an optimization method based on finite element simulation that can be used to find the lowest transmission error in the development and design stage of helical gears. The research on vibration and noise of helical gears in China is relatively late and backward. In 1998, He Yunru et al. revealed the mechanism of vibration and noise of helical gears and gear boxes through experimental research, and gave important suggestions on how to control noise. In 2000, Liu Yuyou proposed the power flow method for vibration and noise control of helical gear box at the first international mechanical engineering academic conference. This theory can not only be used to predict the power flow of the entire helical gear transmission system, but also evaluate the vibration response of each subsystem. The system dynamic information obtained by this method can identify the areas with strong vibration and noise of related components, Therefore, some measures are purposefully taken to improve the vibration and noise performance of the gearbox. In 2003, Zhu Ge carried out a systematic study on gearbox gear noise, and proposed the research route of helical gear vibration noise mechanism analysis → identification of sound source → improvement of human hearing characteristics → establishment of sound quality evaluation model, which marked that domestic research on helical gear vibration noise has changed from simple mechanical noise reduction to more high-end sound quality control. In 2008, Wang Chun developed a set of high signal-to-noise ratio fault helical gear vibration signal analysis methods based on wavelet envelope extraction principle and combining wavelet transform and Hilbert change to solve the problem of difficult to distinguish the characteristic signals in high-frequency signals and noises. In 2012, Jiao Yinghou and others carried out numerical calculation and simulation research on the radiated sound field of large vertical gearbox based on FEM and BEM methods, and finally demonstrated its feasibility through experiments. In 2014, based on the four cylinder four stroke gasoline engine and automobile gearbox, Wang Liansheng deeply analyzed the multi-body coupling dynamics of the gear transmission system, the mechanism of gear knock and squeal noise, and the vibration frequency response by means of theory, simulation and test, aiming at the problems of gear knock noise, helical gear squeal noise, and how to improve the sound quality of automobile gears, Finally, the gear vibration noise is optimized by using multi-objective topology optimization technology. In 2019, Wu Xianhong and others used the professional vibration and noise analysis software LMS to carry out finite element simulation on the vibration and noise of the reducer. They believed that the helical gear was subject to periodic vibration under this working condition, and the vibration was the largest at the upper and lower connection parts of the box. This achievement is helpful for the vibration reduction and noise reduction of the helical gear box.
So far, the means used to predict, evaluate and analyze the vibration and noise of helical gear transmission system have been basically perfect, but people find that no matter how thoughtful the consideration is, the test data can not fully match the theoretical calculation and simulation results. Therefore, domestic and foreign scholars began to focus on improving the accuracy of gear vibration and noise measurement methods. In 2016, Jin X et al. made up for the main defects of the traditional integrated empirical mode decomposition (EEMD) method, proposed an adaptive EEMD method based on the influence factors of mode aliasing, which greatly improved the accuracy and efficiency of identification of helical gear vibration noise signals. In 2017, Li D et al. collected the non-stationary vibration signals of the first order planetary gearbox under complex working conditions based on the integrated empirical mode decomposition (EEMD) method, and conducted envelope spectrum analysis on the effective IMF components of the vibration signals, thus improving the detection accuracy of the fault characteristic frequency of the planetary gearbox; Jiao W et al. proposed a time feature extraction method that comprehensively considers independent component analysis (ICA) and a frequency domain feature extraction method of forward least squares approximation support vector machine (FLS-SVM), thus improving the effectiveness of fault diagnosis methods for helical gear boxes; Fang Y et al. put forward a set of methods for measuring the sound quality of electric vehicle powertrain, aiming at the problem that the traditional vehicle noise evaluation methods can not meet the requirements of electric vehicles. At the same time, they increased the feasibility of measuring the sound quality of helical gear vibration noise. In 2019, Wu X et al. used echo state network (ESN) modeling to study the monitoring and data acquisition (SCADA) method of helical gearbox vibration data. Based on the model residual evaluation and dynamic threshold setting theory, the accuracy of complex vibration data detection was improved.