Signal Analysis of Mill Shell Vibration Based on Variational Modal Decomposition

Ball mill is a key heavy energy consuming equipment in the grinding process. It is based on the closed rotation operation mode and the tens of thousands of steel balls loaded inside it to realize the crushing effect on ore. The vibration signals generated by the impact of steel balls with different size distributions on the mill shell with different amplitudes and frequencies contain rich information related to the mill load parameters. The inherent non-stationary and non-linear characteristics of shell vibration signals make it difficult to extract valuable features, and the physical meaning of different characteristic frequency bands is even more difficult to explain. Although the empirical mode decomposition (EMD) algorithm and its improved version can adaptively decompose the vibration signals of the mill shell, there are problems such as mode aliasing. This paper presents a method for analyzing vibration signals of mill shell based on variational mode decomposition (VMD). Firstly, the number of layers K of VMD is determined according to the existing research results. Then, time and frequency domain analysis are performed on the decomposed IMFs. Finally, the contribution of different IMFs is analyzed based on the predictive performance of simple linear models. The effectiveness is shown by the vibration signal of the experimental mill.