Aiming at the problems of large vibrations and noise of a working stalk rubbing machine, this paper took the 9R-60 rubbing machine as the research object and used the B&K modal test system and the vibration test system to analyse the modal and no-load conditions of the whole machine. Through analysing modal test data, it was concluded that the first five natural frequencies of the machine were 95.262 Hz, 144.386 Hz, 288.198 Hz, 313.719 Hz and 326.140 Hz. The results showed that spindle rotation had a more significant effect on the vibration than the feed chain rotation; the maximum vibration acceleration occurred at the small motor frame at a spindle speed of 1700 r·min-1 and a feed chain speed of 0.65 m·s-1, which was 135.539 m·s-2. The distribution of the amplitude statistical characteristics of the vibration signals follows the normal distribution and belongs to the stationary random process. The vibration was a self-excited vibration of the rotating machinery caused by the rotation of the main shaft and a forced vibration excited by the rotation of the same shaft. The research provides a direction for further research on the vibration characteristics of the rubbing machine under load conditions, and provides a theoretical basis for the subsequent vibration reduction design.

Larger vibration and noise often exist in agricultural machinery due to the harsh working environment and high power. The rubbing machine is one of the indispensable pieces of equipment in the agriculture and livestock industry, and it is affected by the vibration of large constraints on its promotion and use. To reduce the vibration of the rubbing machine, the vibration characteristics of the spindle rotor were first analysed by modal simulation, thus determining the larger contributions to the spindle rotor vibration. Second, aluminium foam material was installed in the large deformation part of the spindle rotor. Its vibration reduction and energy absorption characteristics were used to optimise the vibration reduction design by increasing the damping. Third, a steel ball impact test was conducted to analyse the vibration characteristics of the optimised spindle rotor. The results show that the maximum impact accelerations were reduced by 28.4% and 64.75% in the axial and radial directions, respectively, and the impact energies were reduced by 67.3% and 90.65% in the axial and radial directions within 2 s of impact collision, respectively, indicating that the optimised spindle rotor damping increased significantly. In addition, the vibration reduction effect of the optimised rubbing machine was verified by a bench test. By measuring the change degree of the static component of the spindle rotor vibration, the axial, radial, and vertical vibrations of the spindle rotor were improved by 5.78%, 10.32%, and 23.96%, respectively. Therefore, optimising the spindle rotor with aluminium foam material can reduce the vibration generated during the impact of the material on the spindle rotor. The rubbing machine’s vibration, damping, and energy absorption were also realised in real working conditions.

Since Bitcoin came into the world, modelling and analyzing the underlying characteristics of Bitcoin has attracted increasing attention. This paper uses a framework including decomposition, reconstruction and extraction method (DRE) to analyze price fluctuations based on ultra-high-frequency data from Dec.1, 2019, to Nov.30, 2021. First, the ensemble mode decomposition (EMD) is employed to decompose the Bitcoin hourly spot price into 13 intrinsic mode functions (IMF) plus a residual. Second, the IMFs are reconstructed into high-frequency components, low-frequency components and a trend based on fine-to-coarse reconstruction. Furthermore, the intraday volatility analysis based on LM test is applied on 15-minutes frequency data to detect discontinuous jump arrivals and extract jump from realized quadratic variation. Empirical results show that three components of reconstruction can be identified as short term fluctuations process caused by microstructure noise, the shocks affected by major events, and a long-term trend based on inelastic supply and rigid demand. We find that approximately 40% of jumps can be matched with the news from the public news database (Factiva), and the jump sizes are larger than that of stock markets. This finding indicates that the Bitcoin market has more irregularly noise and unforeseen shocks from unscheduled events.