At present, air pollution caused by heavy industrial products such as iron and steel, thermal power generation and cement is still very serious in China. The main reason is the low dust removal effect of PM2.5 and PM10 particles. To solve the problem of difficult treatment of fine dust in converter flue gas, the collaborative treatment method based on acoustic waves and chemical agglomeration was used to pretreat converter flue gas dust in an evaporative cooler to improve the dust removal efficiency of fine dust. Single-factor experiment and orthogonal experiment were used to study the agglomeration effect of fine dust under different factors, such as the type of flocculants [acrylamide (PAM), sodium carboxymethyl cellulose (CMC) and xanthan gum (XTG)], flocculant concentration, acoustic frequency and acoustic field time. The results of the single-factor experiment showed that the agglomeration effect of the three flocculants was PAM>CMC>XTG from large to small, taking the increase of the peak particle size of the fine dust as the evaluation standard. The agglomerating effect was the best when the concentration of agglomerating agent was 0.1 g/L, the effect was obvious when the acoustic frequency was 33 kHz, and the effect was the best when the acoustic residence time was 15 s. The synergistic effect of the acoustic wave and chemical agglomeration was better than that of chemical agglomeration and acoustic wave alone. The results of the orthogonal experiment showed that when the concentration was 0.1 g/L, the acoustic frequency was 33 kHz, and the acoustic residence time was 15 s, the agglomeration effect was the most significant. The peak particle size increased from 3.311 μm to 43.59 μm, and the dust removal efficiency of the corresponding electrostatic precipitator reached 97%. From the experimental comparison of the coordination mechanism and the single agglomeration mechanism, the synergetic mechanism combined the advantages of a single agglomeration mechanism such as chemistry and acoustic waves, and provided a feasible basis for multi-mechanism dust removal in the industry. The results can provide reliable basic data for improving the removal of fine dust in the flue gas of iron and steel production, and lay a foundation for improving the removal efficiency of fine dust in the industrial flue gas.