Frequency domain coherence analysis and relationship recognition between gearbox vibration and input energy signal

Abstract: From the perspective of energy, vibration of gearbox and other rotating equipment actually is the energy propagation process. Although vibration signal analysis is the most popular technology to realize fault diagnosis for such equipment, but to broaden the horizons of rotating equipment fault diagnosis technology, the validity of energy signal analysis method was proposed and discussed in this paper. How to shed some further light on the issue through theoretical and experimental study is a prospective research work in this field. Firstly, the relationship between the gearbox transmission energy and vibration signal was analyzed based on the vibration mechanism which revealed that the torque and input power generate gear static transmission error, and then produce the vibration signal. Meanwhile, a general formula was given for calculating the input power of the transmission system, which was used to establish the theory basis for the pre-processing of the original energy data. Secondly, the model of gear transmission energy interact with vibration was proposed to analyze the stable I/O relationship between the input energy and vibration signal response using correlation function based on the probability statistics form. Results showed that the larger of correlation value in the key frequency point, the more obvious of vibration energy dissipation. Finally, the normal and fault gear contrast experiment was carried out in the energy monitoring experimental platform of gear transmission system. Analysis of the experimental power signal spectrum found it is similar to vibration signal that the side band also appeared with the rotating frequency as modulation frequency on the both side of the fault gear's meshing frequencyand typical frequency point distribution with larger amplitude accords with the traditional gear fault characteristic spectrum. Thus the spectrum features of power signal was confirmed consistent with traditional gear fault vibration spectrum, which all could reflect rich frequency information. So, condition of gearbox could also be revealed obviously by using power signal spectrum Meanwhile, auto power spectrum and cross power spectrum of vibration and power signal were all analyzed by using coherent analysis method, and the forecast that they correlate highly was verified based on classical control theory. In conclusion, vibration excitation originated from in gear vibration mechanism analysis filed, and energy had a close relationship with vibration signal. The paper lays an effective foundation for the fault diagnosis technology based on energy signal analysis.