Material identification employing a grating spectrometer
View Patent ↗Multi-ordered spectral data is obtained from various known substances and is stored in a spectral library. The identification of an unknown material is accomplished by correlating the sample's multi-ordered spectrum against all or a portion of the spectrum in the library, and finding the closest match.
1. A method for identifying an unknown material comprising:
obtaining a multi-order spectrum from a sample of said unknown material, wherein the multi-order spectrum comprises a plurality of simultaneously obtained diffraction orders;
comparing the obtained multi-order spectrum to multi-order spectra for known materials; and
outputting an identification of the sample based on a correlation between the multi-order spectrum from the sample and the multi-order spectra for the known materials.
2. The method of claim 1 , further comprising outputting one or more next closest identifications based upon the correlation between the multi-order spectrum from the sample and the multi-order spectra for known compositions.
3. The method of claim 1 , wherein the correlation is a linear and a rank correlation.
4. The method of claim 1 , wherein the correlation is a statistical correlation.
5. The method of claim 1 , further comprising building a library of spectra for the known materials.
6. The method of claim 1 , wherein the comparison can be performed against a spectral library or a portion of a spectral library.
7. The method of claim 1 , wherein the multi-order sample spectrum comprises at least a first and a second order spectra.
8. The method of claim 1 , wherein the multi-order sample spectrum comprises all spectra.
9. The method of claim 1 , further comprising outputting a correlation coefficient.
10. The method of claim 1 , further comprising displaying a summary of the correlation.
11. A system for identifying an unknown material comprising:
a spectrometer adapted to obtain a multi-order spectrum from a sample of said unknown material, wherein the multi-order spectrum comprises a plurality of simultaneously obtained diffraction orders;
a correlation module adapted to compare the obtained multi-order spectrum to multi-order spectra for known materials; and
an output device adapted to output an identification of the sample based on a correlation between the multi-order spectrum from the sample and the multi-order spectra for the known materials.
12. The system of claim 11 , wherein the output device outputs one or more next closest identifications based upon the correlation between the multi-order spectrum from the sample and the multi-order spectra for known materials.
13. The system of claim 11 , wherein the correlation is a linear and a rank correlation.
14. The system of claim 11 , wherein the correlation is a statistical correlation.
15. The system of claim 11 , wherein the output device as adapted to build a library of spectra for the known materials.
16. The system of claim 11 , wherein the comparison can be performed against a spectral library or a portion of a spectral library.
17. The system of claim 11 , wherein the multi-order sample spectrum comprises at least a first and a second order spectra.
18. The system of claim 11 , wherein the multi-order sample spectrum comprises all spectra.
19. The system of claim 11 , wherein the output device determines and outputs a correlation coefficient.
20. The system of claim 11 , wherein the output device cooperates with the correlation module to display a summary of the correlation.
21. A system for identifying an unknown material comprising:
means for obtaining a multi-order spectrum from a sample of said unknown material, wherein the multi-order spectrum comprises a plurality of simultaneously obtained diffraction orders;
means for comparing the obtained multi-order spectrum to multi-order spectra for known materials; and
means for outputting an identification of the sample based on a correlation between the multi-order spectrum from the sample and the multi-order spectra for the known materials compositions.