Passive Open-Path FTIR Measurements and Spectral Interpretations for in situ Gas Monitoring and Process Diagnostics

Cięszczyk, S.

doi:10.12693/aphyspola.126.673

Cited by 14 publications

(7 citation statements)

References 50 publications

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“…Despite the spatial proximity of the two chambers to the EC tower, there are obviously differences in the soil respiration data as well as distinct differences in the temporal behavior, considering the comparison to the EC data. This spatial heterogeneity in soil flux for a grassland site can be caused by the variability in soil moisture, changes in soil fauna composition, and the amount of above-ground biomass (Davidson et al, 2002;Rodeghiero and Cescatti, 2008;Darenova et al, 2016). The data of the Grillenburg experiment supports the approach of combined line-averaging and point measurements: OP-FTIR measurements provided path-integrated values covering assumed spatial concentration variability in a single measurement and yielded spatially averaged concentration values.…”

Section: Applicability Of Combined A-tom and Op-ftir Measurementsmentioning

confidence: 59%

“…The environmental factors driving the spatial variability in soil CO 2 fluxes are still poorly understood (Rodeghiero and Cescatti, 2008). Variability in physical soil properties (e.g., soil moisture, clay content), disturbances in soil fauna, and the amount of above-ground biomass can produce spatial soil respiration heterogeneity also within a more or less homogeneous look-alike grassland site (Davidson et al, 2002;Darenova et al, 2016). Hence, the spatial determination of GHG concentrations only based on point information requires an optimized vertically and horizontally distributed instrumental setup of point sensors.…”

Section: Discussionmentioning

confidence: 99%

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Line-averaging measurement methods to estimate the gap in the CO<sub>2</sub> balance closure – possibilities, challenges and uncertainties

Ziemann¹,

Starke²,

Schütze³

2017

Preprint

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Abstract. An imbalance of surface energy fluxes using the eddy covariance (EC) method is observed in global measurement networks although all necessary corrections and conversions are applied to the raw data. Mainly during nighttime, advection can occur resulting in a closing gap that consequently should also affect the CO2 balances. There is the crucial need for representative concentration and wind data to measure advective fluxes. Ground-based remote sensing techniques are an ideal tool as they provide the spatially representative CO2 concentration together with wind components within the same voxel structure. For this purpose, the presented SQuAd (Spatially resolved Quantification of the Advection influence on the balance closure of greenhouse gases)-approach applies an integrated method combination of acoustic and optical remote sensing. The innovative combination of acoustic travel-time tomography (A-TOM) and open-path Fourier transform infrared spectroscopy (OP-FTIR) will enable an upscaling and enhancement of EC measurements. OP-FTIR instrumentation offers the significant advantage of real-time simultaneous measurements of line-averaged concentrations for CO2 and other greenhouse gases (GHGs). A-TOM is a scalable method to remotely resolve 3D wind and temperature fields. The paper will give an overview about the proposed SQuAd-approach and first results of experimental tests at the FLUXNET site Grillenburg in Germany. Preliminary results of the comprehensive experiments reveal a mean nighttime horizontal advection of CO2 of about 10 μmol m−2 s−1 estimated by the spatially integrating and representative SQuAd method. Thereby, uncertainties in determining CO2 concentrations using passive OP-FTIR and wind speed applying A-TOM are systematically quantified. The maximum uncertainty for CO2 concentration was estimated due to environmental parameters, instrumental characteristics, and retrieval procedure with a total amount of approx. 30 % for a single measurement. Instantaneous wind components can be derived with a maximum uncertainty of 0.3 m s−1 depending on sampling, signal analysis, and environmental influences on sound propagation. After the application of averaging over a period of 30 minutes, the standard error of the mean values can be decreased by a factor of at least 0.5 for OP-FTIR and 0.1 for A-TOM depending on the required spatial resolution. The presented validation of the joint application of the two independent, non-intrusive methods is in the focus of attention concerning their ability to quantify advective fluxes.

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Section: Applicability Of Combined A-tom and Op-ftir Measurementsmentioning

confidence: 59%

Section: Discussionmentioning

confidence: 99%

Line-averaging measurement methods to estimate the gap in the CO<sub>2</sub> balance closure – possibilities, challenges and uncertainties

Ziemann¹,

Starke²,

Schütze³

2017

Preprint

View full text Add to dashboard Cite

show abstract

“…This technology has significant research applications in environmental monitoring [4], garbage classification [5], and life chemistry [6]. The Fourier transform infrared spectrometer (FT-IR spectrometer) [7][8][9] is an important means of measuring infrared spectra. It obtains interferogram through an interferometer and restores the interferogram to spectrogram based on Fourier transform.…”

Section: Introductionmentioning

confidence: 99%

An Aero-Engine Classification Method Based on Fourier Transform Infrared Spectrometer Spectral Feature Vectors

Du,

Han,

Shi

et al. 2024

Electronics

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Aiming at the classification identification problem of aero-engines, this paper adopts a telemetry Fourier transform infrared spectrometer to collect aero-engine hot jet infrared spectrum data and proposes an aero-engine classification identification method based on spectral feature vectors. First, aero-engine hot jet infrared spectrum data are acquired and measured; meanwhile, the spectral feature vectors based on CO2 are constructed. Subsequently, the feature vectors are combined with the seven mainstream classification algorithms to complete the training and prediction of the classification model. In the experiment, two Fourier transform infrared spectrometers, EM27 developed by Bruker and a self-developed telemetry FT-IR spectrometer, were used to telemeter the hot jet of three aero-engines to obtain infrared spectral data. The training data set and test data set were randomly divided in a ratio of 3:1. The model training of the training data set and the label prediction of the test data set were carried out by combining spectral feature vectors and classification algorithms. The classification evaluation indicators were accuracy, precision, recall, confusion matrix, and F1-score. The classification recognition accuracy of the algorithm was 98%. This paper has considerable significance for the fault diagnosis of aero-engines and classification recognition of aircrafts.

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“…The vibrations and rotations of these molecules form a specific infrared absorption and emission spectrum. Fourier Transform Infrared Spectrometer (FT-IR Spectrometer) [7][8][9] is an important means to measure infrared spectrum. Interferogram is 2 obtained through interferometer.…”

Section: Introductionmentioning

confidence: 99%

CWT-AM-CNN: A Lightweight Feature Extraction Network with Attention Mechanism Based on CWT Peak Seeking Method for Aero-Engine Hot Jet FT-IR Classification

Du,

Han,

Kang

et al. 2024

Preprint

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Focusing on the problem of identifying and classifying aero-engine models, this paper measures the infrared spectrum data of aero-engine hot jets using a telemetry Fourier transform infrared spectrometer. Simultaneously, infrared spectral data sets with the six different types of aero-engines are created. For the purpose of classifying and identifying infrared spectral data, a CNN architecture based on the continuous wavelet transform peak seeking attention mechanism (CWT-AM-CNN) is suggested. This method calculates the peak value of middle wave band by continuous wavelet transform, and the peak data is extracted by the statistics of the wave number locations with high frequency. Attention mechanism is used for the peak data, and the attention mechanism is weighted to the feature map of the feature extraction block. The training set, vali-dation set and prediction set are divided in the ratio of 8:1:1 for the infrared spectral data sets. For three different data sets, CWT-AM-CNN proposed in this paper is compared with the classical classifier algorithm based on CO2 feature vector and the popular AE, RNN and LSTM spectral processing networks. The prediction accuracy of the proposed algorithm in the three data sets is as high as 97%, and the lightweight network structure design not only guarantees high precision, but also has a fast running speed, which can realize the rapid and high-precision classification of the infrared spectral data of the aero-engine hot jets.

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Passive Open-Path FTIR Measurements and Spectral Interpretations for in situ Gas Monitoring and Process Diagnostics

Cited by 14 publications

References 50 publications

Line-averaging measurement methods to estimate the gap in the CO<sub>2</sub> balance closure – possibilities, challenges and uncertainties

Line-averaging measurement methods to estimate the gap in the CO<sub>2</sub> balance closure – possibilities, challenges and uncertainties

An Aero-Engine Classification Method Based on Fourier Transform Infrared Spectrometer Spectral Feature Vectors

CWT-AM-CNN: A Lightweight Feature Extraction Network with Attention Mechanism Based on CWT Peak Seeking Method for Aero-Engine Hot Jet FT-IR Classification

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Passive Open-Path FTIR Measurements and Spectral Interpretations for in situ Gas Monitoring and Process Diagnostics

Cited by 14 publications

References 50 publications

Line-averaging measurement methods to estimate the gap in the CO&lt;sub&gt;2&lt;/sub&gt; balance closure – possibilities, challenges and uncertainties

Line-averaging measurement methods to estimate the gap in the CO&lt;sub&gt;2&lt;/sub&gt; balance closure – possibilities, challenges and uncertainties

An Aero-Engine Classification Method Based on Fourier Transform Infrared Spectrometer Spectral Feature Vectors

CWT-AM-CNN: A Lightweight Feature Extraction Network with Attention Mechanism Based on CWT Peak Seeking Method for Aero-Engine Hot Jet FT-IR Classification

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Product

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Line-averaging measurement methods to estimate the gap in the CO<sub>2</sub> balance closure – possibilities, challenges and uncertainties

Line-averaging measurement methods to estimate the gap in the CO<sub>2</sub> balance closure – possibilities, challenges and uncertainties