Robust Classifier for the Automated Detection of Ammonia in Heated Plumes by Passive Fourier Transform Infrared Spectrometry
| Autor: | Mukire J. Wabomba, Gary W. Small |
|---|---|
| Rok vydání: | 2003 |
| Předmět: |
Analyte
Spectrometer Analytical chemistry Air Pollutants Occupational Linear discriminant analysis Fourier transform spectroscopy Analytical Chemistry Sulfur hexafluoride chemistry.chemical_compound symbols.namesake Fourier transform chemistry Ammonia Robustness (computer science) Spectroscopy Fourier Transform Infrared Solvents symbols Biological system Digital filter |
| Zdroj: | Analytical Chemistry. 75:2018-2026 |
| ISSN: | 1520-6882 0003-2700 |
| DOI: | 10.1021/ac026105x |
| Popis: | An automated classification algorithm is implemented for the detection of ammonia vapor in heated plumes by passive Fourier transform infrared (FT-IR) spectrometry. This classification methodology allows the real-time detection of chemical signatures in gaseous effluents such as those generated from industrial processes. The characteristics of real-time implementation and excellent robustness are achieved by an analysis strategy based on the application of band-pass digital filters to short segments of the interferogram data collected by the FT-IR spectrometer, followed by the use of piecewise linear discriminant analysis to obtain a yes/no classification regarding the presence of the analyte signature in the filtered data. The optimal classifier developed through this work is based on only 110 interferogram points and employs a single band-pass filter centered at 945 cm(-)(1) with a pass-band full width at half-maximum of 93 cm(-)(1). The average stop-band attenuation of the optimal filter is 42.1 dB. The robustness of the algorithm is tested by exposing it to chemical releases of sulfur hexafluoride, ethanol, methanol, sulfur dioxide, and hydrogen chloride that were not included in the development of the classifier. Excellent classification performance is demonstrated, with missed ammonia detections occurring at a rate of approximately 1%. The occurrence of false detections is less than 0.1% for SF(6) and less than 0.02% for the other interferences tested. |
| Databáze: | OpenAIRE |
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