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超音速火焰噴涂鐵基非晶納米晶涂層的工藝參數與性能試驗

Experimental study on spray parameters and properties of HVOF sprayed Fe-based amorphous nanocrystalline coating

  • 摘要: 為了進一步深入研究鐵基非晶涂層的制備和性能,利用人工神經網絡和多因素多水平設計對超音速火焰噴涂技術制備的鐵基非晶納米晶涂層的工藝參數和性能進行了優化,以期對鐵基非晶涂層的實際應用提供參考. 多因素多水平試驗通過設計分析方法和設計實驗參數,建立神經網絡模型,研究了煤油量、氧氣量、送粉率和噴涂距離四項工藝參數對涂層孔隙率、硬度、結合強度和沉積效率的影響規律. 采用掃描電鏡、透射電鏡等手段表征了粉末及涂層的顯微結構和內部微觀組織形貌;采用X射線衍射儀、同步熱分析儀等設備對粉末和涂層成分、相組成和非晶程度進行了觀察分析. 驗證了工藝參數優化過程的計算機模擬結果,確定了最佳噴涂工藝參數范圍,進一步提升了涂層的性能. 討論了噴涂過程中孔隙形成的微觀過程和非晶納米晶對涂層性能的影響機理. 研究表明各工藝參數對涂層性能是多因素互相影響的,理論上最佳噴涂工藝參數為煤油量23 L·h?1、氧氣量51 L·h?1、送粉率72 g·min?1、噴涂距離280 mm,制備出的鐵基非晶涂層厚度約為270 μm、孔隙率約為1.3%、結合強度約為84 MPa、硬度約為1110 HV0.3. 涂層非晶程度在80%左右,納米晶尺寸為3~5 nm, 涂層在600 ℃以下不會發生晶化過程.

     

    Abstract: This study demonstrates the benefits of high-quality and high-efficiency supersonic flame spraying, aids smart decision-making, and lays a theoretical basis for the practical application of iron-based amorphous coatings. By implementing an artificial neural network, a comprehensive design study that considers several factors and levels may effectively direct the optimization of process parameters, improve product surface performance, minimize expenses, and boost efficiency. This enables the raw materials to attain maximum efficiency in real-world applications. This work examined the technological parameters and properties of Fe-based amorphous nanocrystalline coating using supersonic flame spraying technology, utilizing a multi-factor and multi-level design analysis approach to conduct experimental parameter design. A BP neural network model was developed to investigate the impact of coal oil quantity, oxygen quantity, powder feeding rate and spraying distance on the porosity, hardness, bonding strength, and deposition efficiency of the coating. The powder and coating’s microstructures were analyzed using scanning electron microscopy and transmission electron microscopy. In addition, X-ray diffraction, synchronous thermal analysis, and other techniques were employed to observe and analyze the phase constitution and amorphous content of both the powder and the coating that was created. The computer simulation results were validated while optimizing the process parameters. The measurement of the ideal spraying process parameter range further improved the coating performance. The text discusses the mechanism of pore development at a microscopic level during spraying, as well as the connection between the formation principle of amorphous nanocrystalline and the coating performance. The results revealed that several components have mutual influence on the coating. Theoretically, the most favorable spray parameters for achieving optimal coating are as follows: a diesel flow rate of 23 L·h?1, oxygen flow rate of 51 L·h?1, a powder feeding rate of 72 g·min?1, and a spraying distance of 280 mm. To develop a high quality coating of Fe-based amorphous alloy that improves material surface performance, one must carefully select a suitable spraying material and employ the proper thermal spraying procedure. The coating yielded the following results: a thickness of 270 μm, a porosity of 1.3%, a binding strength of 80 MPa, and a hardness of 1110 HV0.3. The amorphousness degree of the coating was exhibited around 80%, with a nanocrystalline diameter was ranging from 3–5 nm. Crystallization of the coating is only possible above 600 ℃.

     

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