With the evaporation of water vapor in industrial boilers, a large amount of calcium and magnesium ions are left in the boiler water. If not treated, scale will form in the water-cooled tubes, causing tube explosion and boiler shutdown. In order to ensure the safe operation of the equipment and eliminate potential safety hazards, the calcium and magnesium scale in the boiler is removed by maintaining a certain amount of phosphate ions in the water.The traditional detection techniques for phosphate ions mainly include colorimetry, spectrophotometry, chromatography, potentiometry, etc. These methods have cumbersome and time-consuming preliminary processing steps. The spectroscopic method is an analytical method to quantify the concentration of a substance by measuring the absorption spectrum and establishing a mathematical model of the relationship between the concentration and the substance. A method for rapidly measuring phosphate ions based on ultraviolet absorption spectroscopy and the SPA-ELM algorithm was proposed. According to the water quality parameter requirements before entering the hot water boiler stipulated in “Industrial Boiler Water Quality GB/T 1576—2018”, 37phosphate ion solutions with the concentration range of 5~100 mg·L-1 were prepared, and the UV absorption spectrum was collected using the established experimental equipment. The training and test sets were divided randomly according to the ratio of 7∶3 by SPXY. Data were preprocessed by Savitzky-Golay (S-G) filtering to improve the signal-to-noise ratio of the spectrum. The dimensionality of the spectrum was reduced by Successive Projection Algorithm(SPA). Five characteristic wavelengths strongly correlated with phosphate ionswere screened out. Finally, the Extreme Learning Machine(ELM) was used to fit the absorbance at the characteristic wavelength with the sample concentration, and the regression model of phosphate ions was established withR2 and RMSE as the evaluation indexes of the model. TheR2 and RMSE of the training set established by the method proposed in this paper are 0.997 2 and 1.301 5 mg·L-1, and theR2 and RMSE of the test set are 0.999 5 and 0.517 4 mg·L-1. In order to verify the effect of the SPA-ELM prediction model proposed, four other prediction models, LASSO-ELM, PCA-ELM, SPA-PLS and SPA-SVR, were established for comparison. The experimental results show that theR2 and RMSE of the prediction model established by SPA-ELM are better than those.It shows that both the feature selection and regression methods adopted in this paper are optimal. The modelling method adopted in this paper can accurately predict the water with phosphate concentration ranging from 5 to 100 mg·L-1, which provides a new solution for detecting phosphate ions in water.