Random vibration study of cold rolling mill excited by different hardness of strip steel

Abstract

Purpose:

The hardness of individual steel strips demonstrates inherent variability in actual production processes. Systematic hardness testing must be conducted to investigate the distribution patterns of strip hardness. Furthermore, analyzing the random vibration characteristics of cold rolling mill models under varying strip hardness conditions is essential for elucidating the complex vibration mechanisms involved in rolling operations. This investigation offers critical insights into establishing correlations between material properties and dynamic responses in industrial rolling processes.

Methods:

The surface hardness of the strip was first systematically measured using standardized Vickers testing. Subsequent statistical analysis, employing Gaussian probability distribution principles, verified the hardness measurements’ stochastic characteristics. This probabilistic characterization provided essential load input parameters (PSD data) for the cold rolling mill system’s finite element-based random vibration analysis. The established three-dimensional model was imported into ANSYS Workbench software to construct the framework for the random vibration analysis. Utilizing the modal superposition method, boundary conditions were defined to incorporate the statistical characteristics of strip hardness. Finite element simulations were conducted to resolve the probability density distributions of mill vibration responses under varying strip hardness conditions. Post-processing in MATLAB enabled a quantitative analysis of power spectral density (PSD) responses, establishing correlations between strip surface hardness parameters and dynamic vibration characteristics.

Results:

Surface hardness measurements of the three strips demonstrated significant inter-sample variability. Statistical analysis revealed that while the hardness fluctuations followed Gaussian distribution patterns, notable discrepancies were observed in probability distribution skewness and statistical central tendencies. When the average surface hardness of the strip decreases, the amplitude and overall frequency range of vibrations in the cold continuous rolling mill diminish. However, specific frequencies (35 Hz, 131 Hz, and 246 Hz) still appear alongside an interesting amplitude dynamic where the lower work roll exhibits higher vibration than the upper one. Additionally, a significant positive correlation exists between surface hardness deviation and both vibration amplitude and frequency range, indicating that larger deviations in surface hardness lead to more pronounced vibrations. This relationship highlights the influence of surface properties on the mechanical behavior of the rolling mill during operation.

Conclusion:

It is of great significance to study the vibration characteristics of the rolling mill and reveal its vibration mechanism, as this research provides insights closer to the actual state of the strip steel surface. The distribution of the strip’s surface hardness significantly impacts the amplitude and frequency range of the rolling mill’s vibrations. As the hardness fluctuation increases, the amplitude and frequency range of the induced vibrations also increase.