Data validation and classification in optical analysis systems
First Claim
1. A method of classifying measurement results in a multivariate optical computing system, the method comprising:
- receiving a first signal based on a first portion of an illumination light that has interacted with a sample, the first signal modified by at least one spectral element;
receiving a second signal based on the first portion of the illumination light;
separating a second portion of the illumination light from a first portion of the illumination light before the first portion of the illumination light has interacted with the sample;
determining a baseline for the first signal and the second signal using a calibration signal from the second portion of the illumination light, the calibration signal modified by the at least one spectral element; and
providing classifying information based on determining if the first signal and the second signal lie in a range of expected results.
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Accused Products
Abstract
A method of classifying information in an optical analysis system includes obtaining calibration data defining a plurality of data points, each data point representing values for two or more detectors when sampling a material used to construct a multivariate optical element. Based on the calibration data, one or more validation models can be developed to indicate one or more ranges of expected results. Validation data comprising the models can be used to compare data points representing values for two or more detectors when performing a measurement of a material to determine if the data points fall within an expected range. Classification data can be generated based on the comparison and, in some embodiments, one or more indicators, such as a confidence level in a measurement, can be provided.
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Citations
29 Claims
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1. A method of classifying measurement results in a multivariate optical computing system, the method comprising:
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receiving a first signal based on a first portion of an illumination light that has interacted with a sample, the first signal modified by at least one spectral element; receiving a second signal based on the first portion of the illumination light; separating a second portion of the illumination light from a first portion of the illumination light before the first portion of the illumination light has interacted with the sample; determining a baseline for the first signal and the second signal using a calibration signal from the second portion of the illumination light, the calibration signal modified by the at least one spectral element; and providing classifying information based on determining if the first signal and the second signal lie in a range of expected results. - View Dependent Claims (2, 3, 4, 6, 7, 8, 19)
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5. A method of classifying measurement results in a multivariate optical computing system, the method comprising:
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receiving a first signal based on light that has interacted with a material of interest and at least one spectral element; receiving a second signal based on light that has interacted with the material of interest; and providing classifying information based on determining if the first signal and the second signal lie in a range of expected results; wherein the validation data comprises data indicating at least one boundary that defines expected results as a function of the value of the first and second signal; and wherein providing classifying information comprises determining where a given pair of simultaneous values for the first and second signal lie relative to the at least one boundary. - View Dependent Claims (22, 23)
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9. An optical computing system comprising at least one computing device, the at least one computing device adapted to:
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receive data from a first detector indicative of a first portion of an illumination light that has interacted with a sample, the first signal modified by at least one spectral element; receive data from a second detector indicative of the first portion of the illumination light; separating a second portion of the illumination light from a first portion of the illumination light before the first portion of the illumination light has interacted with the sample; determining a baseline for the data from the first and second detectors using a calibration signal from the second portion of the illumination light, the calibration signal modified by the at least one spectral element; and produce classification data based on determining if the data from the first and second detectors lie in a range of expected results. - View Dependent Claims (10, 12, 13, 14, 15, 16)
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11. An optical computing system comprising at least one computing device, the at least one computing device adapted to:
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receive data from a first detector indicative of light that has interacted with a material of interest and at least one spectral element; receive data from a second detector indicative of light that has interacted with the material of interest; and produce classification data based on determining if the data from the first and second detectors lie in a range of expected results; wherein the at least one computing device is further adapted to access validation data and to produce classification data based on evaluating the data from the first and second detectors and the validation data; wherein the validation data comprises data indicating at least one boundary that defines expected results as a function of the value of the first and second signal; and wherein producing classification data comprises determining where a given pair of simultaneous values for the first and second signal lie relative to the at least one boundary. - View Dependent Claims (24, 25)
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17. A method of configuring a measurement system, the method comprising:
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obtaining calibration data, the calibration data comprising a plurality of data points; based on the calibration data, constructing at least one multivariate optical element based on the data points; based on the data points, preparing a validation model, the validation model comprising a boundary of values dividing an area into a valid result area and an invalid result area; including the at least one multivariate optical element in a measurement system comprising at least one controller; and configuring the at least one controller to validate measurement results based on the validation model. - View Dependent Claims (18)
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20. A method of classifying measurement results in a multivariate optical computing system, the method comprising:
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receiving a first signal based on a first portion of an illumination light that has interacted with a material of interest, the first signal modified by at least one spectral element; receiving a second signal based on the first portion of the illumination light; providing classifying information based on determining if the first signal and the second signal lie in a range of expected results; and determining a baseline of at least one of the first signal and the second signal using a second portion of the illumination light, wherein; the second portion of the illumination light is separated from the first portion of the illumination light before the first portion of the illumination light has interacted with the sample. - View Dependent Claims (26, 27)
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21. An optical computing system comprising at least one computing device, the at least one computing device adapted to:
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receive data from a first detector indicative of a first portion of an illumination light that has interacted with a sample, the first signal modified by at least one spectral element; receive data from a second detector indicative of the first portion of the illumination light; determine a baseline for at least one of the data from a first detector and the second detector using data indicative of a second portion of the illumination light, wherein; the second portion of the illumination light is separated from the first portion of the illumination light before the first portion of the illumination light has interacted with the sample; and produce classification data based on determining if the data from the first and second detectors lie in a range of expected results. - View Dependent Claims (28, 29)
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Specification