Planetary gearbox based on EEMD symmetric differential energy spectrum

Because the wind turbine often works in the harsh environment, the number of units is too much, so the fault accidents of the unit are very frequent, and the failure rate increases with the working time. Due to the high cost of repair and maintenance of wind turbine, condition monitoring and fault diagnosis of wind turbine are very important.

By analyzing the vibration signal model of planetary gearbox, Feng Zhipeng put forward the theoretical basis of amplitude demodulation method, and analyzed the envelope spectrum characteristics of different types of vibration signals. Zhao Lei et al. Extracted the envelope signal of planetary gearbox vibration signal based on spectral kurtosis, and realized the extraction of planetary gearbox fault characteristics by adding window method in angular domain. Wang Youren et al. Proposed to calculate the instantaneous frequency of the signal by nonlinear short-time Fourier transform, and then carry out the angular domain modal decomposition to realize the fault diagnosis of the variable speed planetary gearbox

Break. Liu Haohua et al. Extracted the local damage characteristic frequency of gear through EEMD and frequency demodulation, and identified the location of gear crack damage in planetary gearbox. Wang Tianjin et al. Used Teager energy operator method to identify bearing fault characteristic frequency, and compared with envelope spectrum method, the effectiveness of the method was verified. Li Kangqiang et al. Decompose the signal into single component by empirical mode decomposition, and then estimate the amplitude envelope and instantaneous frequency of the modulation signal by generating differential equation method, so as to realize demodulation analysis. By analyzing the sound signal of the fault bearing, Liu Jing demodulated the signal with Teager energy operator, and then analyzed the envelope spectrum, so as to realize the fault diagnosis of the bearing. Leng Junfa and others used the empirical mode to decompose the single component of the signal, and then demodulated the Teager energy operator to extract the fault characteristic frequency of the gear successfully. When dealing with the bearing fault signal, Yang Wenzhi et al. Proposed a demodulation method combining autocorrelation noise reduction and symmetric differential energy operator to solve the problem of inaccurate frequency in the signal processing of energy operator demodulation. All of the above methods do not use symmetric differential energy operator demodulation method to solve the fault diagnosis of planetary gear.

The feature frequency of planetary gear fault is extracted by combining EEMD with symmetrical differential energy operator demodulation. By comparing with the combination effect of EMD and symmetric differential energy operator demodulation, it is found that the frequency components are mainly distributed in meshing frequency and its harmonic frequency. Therefore, the law of the characteristic frequency of planetary gear failure in meshing frequency and its multiple frequency is found, so as to judge whether the planetary gear box is faulty.

ZHY Gear takes planetary gear box as the research object, because of the complexity of vibration signal of planetary gear fault. Therefore, the fault features of planetary gear are effectively extracted by combining EEMD with symmetrical differential energy operator demodulation. Compared with the combination effect of EMD and symmetric differential energy operator demodulation, it is found that the frequency components are mainly distributed in the meshing frequency and its frequency doubling law. From the demodulated spectrum, we can judge whether the broken planetary gear is in fault frequency according to whether the meshing frequency and the side band near the double frequency exist in the interval frequency, so as to realize the purpose of fault diagnosis. It can be seen that the frequency of planetary gear fault can be used as an indicator of planetary gear fault to achieve fault diagnosis.

spacer