Ensemble Prediction Model for Dust Collection Efficiency of Wet Electrostatic Precipitator

WESPs (Wet Electrostatic precipitators) are mainly installed in industries and factories where PM (particulate matter) is primarily generated. Such a wet type exhibits very excellent performance by showing collection efficiency of 97 to 99%, but the may decrease rapidly due situation which dust collector discharge electrode corroded water. Thus, developing technology predict efficient design operation critical. Previous studies have developed machine learning-based models atmospheric concentrations using data measured meteorological agencies. However, analysis for predicting industrial facilities insufficient. In this study, was installed, experiments were conducted. Nonlinear such as operating conditions measurements collected, ensemble prediction developed. According research results, random forest model yielded performance, with best results achieved when target 7: R2, MAE, MSE scores 0.956, 0.747, 1.748, respectively.