In order to solve the problem of difficulty in estimating the powder output of the coal mill in thermal power plants, the soft measurement method is used to establish a BP neural network model combining the system parameters of the coal mill and the powder output of the coal mill, and the relationship between the parameters and the powder output is established. The non-linear mapping relationship is used to estimate the powder output of the coal mill. In order to reduce the error of the model, the WOA-BP algorithm model was established by using the Whale Algorithm (WOA) to optimize the weights and thresholds of the BP neural network. In order to verify the reliability of the WOA-BP algorithm model, the WOA-BP and PSO-BP of the coal mill's powder output were established respectively by the whale algorithm (WOA), particle swarm algorithm (PSO), genetic algorithm (GA) and BP neural network. , GA-BP, BP neural network algorithm model. The research results show that among the four algorithm models, the WOA-BP algorithm estimation model has the best prediction ability for the powder output of the coal mill, and the average absolute error is only 0.94.