DIAGNOSTICS OF FATIGUE CRACK IN ULTERIOR PLACES OF LARGER-SCALE OVERLOADED SUPPORTING SHAFT BASED ON TIME SERIES AND NEURAL NETWORKS

To improve the diagnosis accuracy and self-adaptability of fatigue crack in ulterior place of the supporting shaft, time series and neural network are attempted to be applied in research on diag-nosing the fatigue crack’s degree based on analyzing the vibration characteristics of the supporting shaft. By analyzing the characteristic parameter which is easy to be detected from the supporting shaft’s exterior, the time series model parameter which is hypersensitive to the situation of fatigue crack in ulterior place of the supporting shaft is the target input of neural network, and the fatigue crack’s degree value of supporting shaft is the output. The BP network model can be built and net-work can be trained after the structural parameters of network are selected. Furthermore, choosing the other two different group data can test the network. The test result will verify the validity of the BP network model. The result of experiment shows that the method of time series and neural network are effective to diagnose the occurrence and the development of the fatigue crack’s degree in ulterior place of the supporting shaft.

Multi-site observation of large-scale eddies in the surface layer of the Loess Plateau

This article aims to build a theory of atmospheric boundary layer turbulence under complex conditions. To achieve this goal, we constructed a multi-site observation and analysis method of atmospheric turbulence based on related principles.This method first requires verification for the ergodicity of the full-scale observation of surface-layer turbulence, which proves that eddies within a scale of 60 min during a four-site observation can easily meet ergodicity. Meanwhile, by applying the second-order structure function for the horizontal wind speed turbulence of a single site and upstream and downstream points, we verified the ergodicity of the turbulence observation. Comparing the turbulence spectrum to the second-order structure function for the horizontal wind speed from the four-site observation, a relatively high accordance was observed, proving the reasonability of the multi-site observation. Moreover, compared to the single-site observation, the four-site observation can improve the estimation accuracy of the surface-layer turbulence spectrum and vertical turbulent flux. As a result, we can describe the threedimensional structure of turbulence more accurately and comprehensively by combining analytical data from single-site and four-site observations. In summary, the multi-site turbulence observation method shows that the horizontal and vertical wind turbulence of the Baimiao plateau has a typical structure of a turbulence spectrum with clear spectral gaps. The result is in accordance with the scale of the turbulence spectral gaps obtained from the 6 h data. The horizontal wind speed is under the influence of the terrain, so its spectrum of large-scale eddies has higher fluctuations, but its spectral gaps can still be clearly distinguished. Although the spectral gaps of the temperature spectrum are not distinguishable, they still have the same scale as the spectral gap of the vertical and horizontal turbulence spectrum. Moreover, the temperature spectrum possesses typical structure characteristics of the boundary-layer turbulence spectrum.