摘要
为了进一步深入研究铁基非晶涂层的制备和性能,利用人工神经网络和多因素多水平设计对超音速火焰喷涂技术制备的铁基非晶纳米晶涂层的工艺参数和性能进行了优化,以期对铁基非晶涂层的实际应用提供参考.多因素多水平试验通过设计分析方法和设计实验参数,建立神经网络模型,研究了煤油量、氧气量、送粉率和喷涂距离四项工艺参数对涂层孔隙率、硬度、结合强度和沉积效率的影响规律.采用扫描电镜、透射电镜等手段表征了粉末及涂层的显微结构和内部微观组织形貌;采用X射线衍射仪、同步热分析仪等设备对粉末和涂层成分、相组成和非晶程度进行了观察分析.验证了工艺参数优化过程的计算机模拟结果,确定了最佳喷涂工艺参数范围,进一步提升了涂层的性能.讨论了喷涂过程中孔隙形成的微观过程和非晶纳米晶对涂层性能的影响机理.研究表明各工艺参数对涂层性能是多因素互相影响的,理论上最佳喷涂工艺参数为煤油量23 L·h-1、氧气量51 L·h-1、送粉率72 g·min-1、喷涂距离280 mm,制备出的铁基非晶涂层厚度约为270μm、孔隙率约为1.3％、结合强度约为84 MPa、硬度约为1110 HV0.3.涂层非晶程度在80％左右,纳米晶尺寸为3～5 nm,涂层在600℃以下不会发生晶化过程.
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 ℃.
基金项目
高档数控机床与基础制造装备科技重大专项(2017ZX04012001)
维普
万方数据