In order to better study the importance of coupling to the driving device of dry powder screw conveyor, the design and calculation of the driving device are carried out in this paper. As the important connecting parts of the driving device: the elastic pin coupling and the drum gear coupling, on the basis of finite element analysis and experimental research, the rotational speed and radial offset of the drum gear coupling are experimentally studied in this paper. The simulation results show that the driving device designed in this paper can meet the actual operation requirements, and the material selection is reasonable, which provides a theoretical basis for future design and engineering practice.
KEYWORDS: Wavelets, Denoising, Interference (communication), Signal processing, Feature extraction, Signal to noise ratio, Reconstruction algorithms, Computer simulations, Signal attenuation, Signal analyzers
Fault detection and diagnosis of Rolling mill have a very significant role in the practical application. Extracting the bearing fault signal from a multicomponent signal mixture using a variety of signal de-noising method is the first problem to diagnose the rolling mill bearing. Rolling mill bearing belongs to the bearing of low speed and heavy loading. Diagnosis is difficult because of the interference signal and the complex fault mechanism. Wavelet packet de-noising method was applied to extract the fault characteristics of vibration signals. The analysis results show that the wavelet packet analysis method can effectively remove mixed in the interference signal of the rolling mill rolling bearing signal. The characteristics of rolling mill rolling bearing fault signal become more obvious, and the fault diagnosis result becomes more accurate.
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