Mathematic modeling and condition monitoring of power station tube-ball mill systems

The paper presents a newly developed nonlinear tube-ball mill model for model based on-line condition monitoring. This mathematical model is derived through analyzing energy transferring, heat exchange and mass flow balances. Evolutionary techniques are adopted to identify the unknown system parameters using the on-site measurement data. The identified system parameters are then validated using multiple on-line measurement data. Validation has been conducted by comparing the measured and simulated values. The results indicate that the model can represent the coal mill dynamics and can be used to predict the mill dynamic performance. Then the model is implemented on-line and it can run on-line along with the real milling process. It is then adopted for on-line condition and safety monitoring, fault detection, and control to improve the efficiency of combustion.