基于微束X射线荧光光谱的新型铸&锻GH4096合金涡轮盘成分分布解析

铸&锻GH4096高温合金涡轮盘拥有高承温能力、高强度、低裂纹扩展速率、高抗疲劳性能等优异性能，是航空发动机的关键热端部件。但由于其合金化程度较高、零件尺寸大、制备工艺复杂等，不可避免会出现成分和组织分布不均匀，一定程度影响涡轮盘的服役性能。微区X射线荧光光谱（μ-XRF）具有微区分辨率高、分析速度快、多元素同步分析、非破坏性等优点，被广泛应用于考古、地质、生物等领域，但对大尺寸高温合金构件的成分分布的研究较少，对于材料各原始位置处的成分定量分布表征也未见报道。本试验通过选择合适的测量条件、优化仪器定量方法，建立了基于微束X射线荧光光谱的新型铸&锻GH4096合金涡轮盘成分分布定量分析方法，并引入了原位统计分析方法对涡轮盘中Cr，Co，Mo，W，Ti，Al，Nb和Ni八种主要元素进行了定量统计分布解析。发现涡轮盘厚度的中心区域内Co，Mo和Ti三种元素从轮毂至轮缘存在较明显的弧形负偏析带，而Ni和Cr两种元素存在弧形正偏析带。另外，涡轮盘径向也存在一定的成分梯度分布，Co，Cr和W三种元素含量从轮毂到轮缘的呈现逐渐降低的趋势，而Mo，Ti和Nb三种元素含量则呈现逐渐上升趋势。对各元素最大偏析度、统计偏析度、统计符合度计算分析后可知，Cr，Co，Mo，W，Ti，Nb和Ni七种元素测量区域内整体偏析程度较小、统计符合度大，在材料元素设计值允许范围内具有较好的成分均匀性。使用火花源金属原位分析仪（OPA-200）对相同测试区域的元素进行了线分布分析，其分析结果与微束荧光光谱得到的分析规律具有较好的一致性，说明大尺寸涡轮盘在热处理过程中存在温度场分布，导致了各元素扩散行为以及显微组织分布的差异，因此不同部位的成分也存在一定偏析。通过对大尺寸的涡轮盘成分进行定量统计分布解析，对于评价新型铸&锻变形GH4096高温合金涡轮盘的成分分布均匀性，解析制备工艺与大尺寸构件成分、组织结构分布的相关性具有重要意义。

Analysis of Composition Distribution of New Cast-Forging FGH4096 Alloy Turbine Disk Based on Microbeam X-Ray Fluorescence Spectroscopy

Cast-forging GH4096 superalloy turbine disk is a key hot end component of aero-engine because of its excellent properties such as high temperature bearing capacity, high strength, low crack growth rate, high fatigue resistance and so on. However, due to its high alloying degree, large part size and complex preparation process, it is inevitable that the composition and microstructure distribution will be uneven, which will affect the service performance of the turbine disk to a certain extent. Micro-area X-ray fluorescence spectroscopy (μ-XRF) has the advantages of high micro-resolution, fast analysis speed, simultaneous analysis of multi-elements, non-destructive and so on, so it is widely used in archaeology, geology, biology and other fields. However, there is little research on the composition distribution of large-size superalloy components, and there is no report on the quantitative distribution of composition at the original location of the material. In this experiment, by selecting suitable measuring conditions and optimizing instrument quantitative method, a new quantitative analysis method of composition distribution of cast-forging GH4096 alloy turbine disk based on microbeam X-ray fluorescence spectroscopy was established, and the in-situ statistical analysis method was introduced to analyze the quantitative statistical distribution of Cr, Co, Mo, W, Ti, Al, Nb and Ni in turbine disk. It is found that Co, Mo and Ti have obvious arc negative segregation zone from hub to flange in the central region of turbine disk thickness, while Ni and Cr have arc positive segregation zone. In addition, there is also a certain composition gradient distribution in the radial direction of the turbine disk. The contents of Co, Cr and W gradually decrease from the hub to the flange, while the contents of Mo, Ti and Nb show a gradual upward trend. After the calculation and analysis of the maximum segregation degree, statistical segregation degree and statistical fitting degree of each element, it is known that the overall segregation degree of Cr, Co, Mo, W, Ti, Nb and Ni elements in the measurement area is small, the statistical coincidence degree is large, and they have better composition uniformity within the allowable range of material element design values. The linear distribution of elements in the same test area was analyzed by spark source metal in-situ analyzer (OPA-200). The analysis results agree with those obtained by microbeam fluorescence spectra, indicating that there is temperature field distribution in large-size turbine disks during heat treatment, which leads to differences in element diffusion behavior and microstructure distribution, so there is some segregation in different parts. Through the quantitative statistical analysis of the composition distribution of the large size turbine disk, it is of great significance to evaluate the uniformity of the composition distribution of the new cast-forging deformed GH4096 superalloy turbine disk and to analyze the correlation between the preparation process and the composition and structure distribution of the significant size components.