Alloy powder cleanliness inspection using computed tomography
A system and method are provided including an inclusion module to receive a powder sample from a powder source; a computed tomography equipment; a memory for storing program instructions; an inclusion processor, coupled to the memory, and in communication with the inclusion module, and operative to execute program instructions to: receive the powder sample; execute a computed tomography (CT) scan process of the received sample to generate a first dataset including one or more images; identify inclusions in the one or more images, via a segmentation process; reconstruct, via a reconstruction process, the identified inclusion into a 3D representation; measure the identified inclusion; mark the inclusions on one or more image slices from the 3D representations; and determine whether the powder source is contaminated based on the one or more marked images. Numerous other aspects are provided.
1. A system comprising:
an inclusion module to receive a powder sample from a powder source;
a computed tomography equipment;
a memory for storing program instructions;
an inclusion processor, coupled to the memory, and in communication with the inclusion module, and operative to execute program instructions to:
receive the powder sample;
execute a computed tomography (CT) scan process of the received powder sample to generate a first dataset including one or more images;
identify inclusions in the one or more images, via a segmentation process;
reconstruct, via a reconstruction process, the identified inclusion into a 3D representation;
measure the identified inclusion;
mark the inclusions on one or more image slices from the 3D representations; and
determine whether the powder source is contaminated based on the one or more marked images.
2. The system of claim 1 , wherein the inclusions are one of high density inclusions and low density inclusions.
3. The system of claim 2 , further comprising program instructions to:
categorize the identified inclusion as a high density inclusion or a low density inclusion.
4. The system of claim 1 , wherein an image volume is reconstructed from the first dataset prior to the segmentation process.
5. The system of claim 4 , wherein the image volume is analysed via a quantitative 3D volumetric analysis.
6. The system of claim 5 , wherein the segmentation process generates one or more images prior to identification of the inclusions.
7. The system of claim 1 , wherein the reconstruction process generates a 3D mesh representation for each inclusion.
8. The system of claim 1 , wherein the measurement of the identified inclusion includes at least one of a size filtering process, an inclusion size process and a shape fitting process.
9. The system of claim 1 , wherein the marked inclusions are ranked in size.
10. A method comprising:
receiving a powder sample from a powder source;
executing a computed tomography (CT) scan process of the received powder sample to generate a first dataset including one or more images;
identifying inclusions in the one or more images, via a segmentation process;
reconstructing, via a reconstruction process, the identified inclusion into a 3D representation;
measuring the identified inclusion;
marking the inclusions on one or more image slices from the 3D representations; and
determining whether the powder source is contaminated based on the one or more marked images.
11. The method of claim 10 , wherein the inclusions are one of high density inclusions and low density inclusions.
12. The method of claim 11 , further comprising:
categorizing the identified inclusion as a high density inclusion or a low density inclusion.
13. The method of claim 10 , further comprising:
reconstructing an image volume from the first dataset prior to the segmentation process.
14. The method of claim 13 , further comprising:
analysing the image volume via a quantitative 3D volumetric analysis.
15. The method of claim 14 , further comprising:
generating, via the segmentation process, one or more 2D images prior to identification of the inclusions.
16. The method of claim 10 , further comprising:
generating a 3D mesh representation for each inclusion.
17. The method of claim 10 , wherein measuring the inclusion includes at least one of a size filtering process, an inclusion size process and a shape fitting process.
18. A non-transient, computer-readable medium storing instructions to be executed by a processor to perform a method comprising:
receiving a powder sample from a powder source;
executing a computed tomography (CT) scan process of the received powder sample to generate a first dataset including one or more images;
identifying inclusions in the one or more images, via a segmentation process;
reconstructing, via a reconstruction process, the identified inclusion into a 3D representation;
measuring the identified inclusion;
marking the inclusions on one or more image slices from the 3D representations; and
determining whether the powder source is contaminated based on the one or more marked images.
19. The medium of claim 18 further comprising:
categorizing the identified inclusion as a high density inclusion or a low density inclusion.
20. The medium of claim 18 , further comprising:
reconstructing an image volume from the first dataset prior to the segmentation process.