Operation Monitoring and Optimization of Industrial Boiler Based on Improved PCA

An operation monitoring and optimization method based on cross-segmented principal component analysis (PCA) is proposed to improve the energy efficiency level of industrial boilers. Firstly, the boiler operation data is divided into different modes according to the load using the modal identification values. Historical data with high thermal efficiency is chosen in each model to construct the principal component model. The operating condition of the boiler is monitored using the multi-mode cross-over method. Then, the boiler's operation condition is tested. When it deviates significantly from the high energy efficiency condition, contribution plots are used to determine the factors that lead to this condition. Finally, the operator is guided to carry out targeted operations to optimize the boiler operation process. The practical application in an industrial boiler shows that this method can effectively identify the boiler's operation condition, detect the specific factors, and significantly improve the energy efficiency level of the boiler.