Computational optimization of the configuration of a spatially resolved spectroscopy sensor for milk analysis
| Autor: | Rodrigo Watté, Ben Aernouts, Robbe Van Beers, Wouter Saeys, Annelies Postelmans |
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| Rok vydání: | 2016 |
| Předmět: |
Optimal design
Mean squared error Scattering Chemistry Spectrum Analysis 010401 analytical chemistry Analytical chemistry Estimator Models Theoretical 01 natural sciences Biochemistry Noise (electronics) 0104 chemical sciences Analytical Chemistry 010309 optics Milk Attenuation coefficient 0103 physical sciences Animals Environmental Chemistry Cattle Fiber Absorption (electromagnetic radiation) Biological system Spectroscopy |
| Zdroj: | Analytica Chimica Acta. 917:53-63 |
| ISSN: | 0003-2670 |
| Popis: | A global optimizer has been developed, capable of computing the optimal configuration in a probe for spatially resolved reflectance spectroscopy (SRS). The main objective is to minimize the number of detection fibers, while maintaining an accurate estimation of both absorption and scattering profiles. Multiple fibers are necessary to robustify the estimation of optical properties against noise, which is typically present in the measured signals and influences the accuracy of the inverse estimation. The optimizer is based on a robust metamodel-based inverse estimation of the absorption coefficient and a reduced scattering coefficient from the acquired SRS signals. A genetic algorithm is used to evaluate the effect of the fiber placement on the performance of the inverse estimator to find the bulk optical properties of raw milk. The algorithm to find the optimal fiber placement was repeatedly executed for cases with a different number of detection fibers, ranging from 3 to 30. Afterwards, the optimal designs for each considered number of fibers were compared based on their performance in separating the absorption and scattering properties, and the significance of the differences was tested. A sensor configuration with 13 detection fibers was found to be the combination with the lowest number of fibers which provided an estimation performance which was not significantly worse than the one obtained with the best design (30 detection fibers). This design resulted in the root mean squared error of prediction (RMSEP) of 1.411 cm(-1) (R(2) = 0.965) for the estimation of the bulk absorption coefficient values, and 0.382 cm(-1) (R(2) = 0.996) for the reduced scattering coefficient values. |
| Databáze: | OpenAIRE |
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