Condition Monitoring of Power Plant Milling Process Using Intelligent Optimisation and Model Based Techniques

A complete multi-segment coal mill model was presented in this chapter. The model considered heat, mass, power balances involved in the milling process. The mill model can represent the whole milling process including the start-up and shut-down periods. Then the model is validated using on-line measurement. By adopting this multi-segment coal mill model in power plants, the power plant engineers will be offered a non-stop model for monitoring the coal mill system The model can estimate the inmeasurable intermediate variables which is very valuable for condition monitoring and fault detection. So the model will contribute for better mill control actions and prediction of system faults. The multisegment model is implemented on-line usiing C++ language. Based on the mathematical model and its on-line implementation, a new diagnose method is introduced to diagnose the mill operation condition. From the current results, the model could predict the uneven mixture of biomass material with coal inside the mill from the variation trend of the key parameters, which can then predict potential fire incidents.