Retrieving CO Concentrations from FT-IR Spectra with Nonmodeled Interferences and Fluctuating Baselines Using PCR Model Parameters

Bak, Jesper

doi:10.1366/0003702011952208

Cited by 7 publications

(6 citation statements)

References 11 publications

(12 reference statements)

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“…In order perform the quantitative analysis of spectra for different concentrations there were applied a spectrum length method (SLM) , which was based on a very simple idea. The main goal of this method is compute the spectrum length by summing up the differences between two adjacent points of analyzed spectrum [1].…”

Section: Methods Appliedmentioning

confidence: 99%

“…For reference spectrum measurements issue, there were developed quantitative methods for measuring analyte concentrations, for instance spectral subtraction method of gas phase FTIR [10] and a single beam titration method [16]. It was developed the spectrum length method applied in gas concentration analysis [1] and was successfully implemented in the context of quantitative analysis of spectra measured by TFBG (Tilted fiber Bragg grating) [6].…”

Section: Quantitative Analysis In Op-ftirmentioning

confidence: 99%

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The Spectrum Length Method in Quantitative Interpretation of Selected Optical Spectra

Wawrzyk

2022

IAPGOS

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Different algorithms are used for the quantitative interpretation of optical spectra. Regression methods e.g CLS (Classical Least Squares) or PLS (Partial Least Squares) are often used in typical problems of laboratory spectroscopy. The spectra analysis is generally a multi-step process, in which, depending on the spectra type, modification of individual regression methods or special dedicated methods are applied. For example, contour length method or spectra length algorithm are used in this purpose. The basic version of the algorithm is very simple in terms of mathematics. It has been proposed for the analysis of spectra in the OP-FTIR open path spectroscopy, where there are significant fluctuations in the spectrum baseline. The spectrum length is a parameter closely related to the content of the analyzed gas component. Independently of spectral length algorithm, a method has been developed in which difference length of two spectra (measured and reference) is used to compare the spectra. The minimum length of the spectral difference is an indicator of their best fitting. The article presents two ways of using the spectrum length: as a direct and indirect parameter indicating the measured quantity on the basis of the spectrum. There were performed the spectrum length algorithm as a digital differentiating filter with a specific frequency response. There were also analyzed more advanced differentiating filter and the possibility of frequency spectrum filter design used in an analysis of optical spectral signal. There were performed the analysis of the spectrum length method in the case of the synthetic calibration involving the use of model spectra from simulations realized by HITRAN database. There were analyzed numerically the problem of the Instrument Line Shape influence on the synthetic spectra and results of the determining the content of components by the minimizing the difference of spectral length.

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Section: Methods Appliedmentioning

confidence: 99%

Section: Quantitative Analysis In Op-ftirmentioning

confidence: 99%

The Spectrum Length Method in Quantitative Interpretation of Selected Optical Spectra

Wawrzyk

2022

IAPGOS

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“…This corresponds to the sum of the first derivative of the function. This algorithm was proposed for the analysis of spectra of FTIR spectrometers [ 32 , 33 ]. The differential equation of a suitable digital filter with a finite impulse response length can be written as follows:

where

is the input signal of the filter, which in the considered aspect is the measured transmission spectrum.…”

Section: Derivatives and Contour Length For Tfbg Spectramentioning

confidence: 99%

A Wavelet Derivative Spectrum Length Method of TFBG Sensor Demodulation

Cięszczyk

Skorupski

Wawrzyk

et al. 2023

Sensors

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Fibre optic sensors using tilted fibre Bragg grating (TFBG) have high sensitivity for refractive index measurements. In order to achieve good metrological parameters of the measurement, an appropriate method of spectrum demodulation must be used. The method proposed in the article is an improvement of the spectral length algorithm. The spectral length parameter is treated as the sum of the derivative filter responses. In the original version, the first difference of spectrum elements was used, while this article proposes to use the wavelet transform to calculate the numerical derivative approximation. The advantage of this solution is an easy way to select the level of smoothing filtration by changing the scale parameter. The derivation is appropriate even for a relatively low signal-to-noise level. The approximation of the spectral length by the derivative calculated using the wavelet transform eliminates the high-frequency noise of the optical signal. The absolute value of determined spectral derivatives after significant smoothing can be used to estimate the wavelength of the decay of modes. After analyzing experimental data and performing calculations, it turns out that this is a linear method with better resolution than the contour length algorithm.

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“…Traditional hyperspectral content prediction models are divided into linear and nonlinear models. Linear models are mostly multiple linear regression (MLR) [32], multiple linear stepwise regression (MLSR) [33], principal component regression (PCR) [34], and partial least squares regression (PLSR) [35]. The commonly used nonlinear models include support vector machine regression [36] and neural network models [37].…”

Section: Introductionmentioning

confidence: 99%

Hyperspectral Prediction Model of Metal Content in Soil Based on the Genetic Ant Colony Algorithm

et al. 2019

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The accumulation of metals in soil harms human health through different channels. Therefore, it is very important to conduct fast and effective non-destructive prediction of metals in the soil. In this study, we investigate the characteristics of four metal contents, namely, Sb, Pb, Cr, and Co, in the soil of the Houzhai River Watershed in Guizhou Province, China, and establish the content prediction back propagation (BP) neural network and genetic-ant colony algorithm BP (GAACA-BP) neural network models based on hyperspectral data. Results reveal that the four metals in the soil have different degrees of accumulation in the study area, and the correlation between them is significant, indicating that their sources may be similar. The fitting effect and accuracy of the GAACA-BP model are greatly improved compared with those of the BP model. The R values are above 0.7, the MRE is reduced to between 6% and 15%, and the validation accuracy is increased by 12–64%. The prediction ability of the model of the four metals is Cr > Co > Sb > Pb. These results indicate the possibility of using hyperspectral techniques to predict metal content.

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Retrieving CO Concentrations from FT-IR Spectra with Nonmodeled Interferences and Fluctuating Baselines Using PCR Model Parameters

Cited by 7 publications

References 11 publications

The Spectrum Length Method in Quantitative Interpretation of Selected Optical Spectra

The Spectrum Length Method in Quantitative Interpretation of Selected Optical Spectra

A Wavelet Derivative Spectrum Length Method of TFBG Sensor Demodulation

Hyperspectral Prediction Model of Metal Content in Soil Based on the Genetic Ant Colony Algorithm

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