Extraction of Feature Photoacoustic Spectroscopy Probed by a Sensor against a Large Background Noise

Zhi Ying Wu; Yi Zhang; Xin He

doi:10.4028/www.scientific.net/AMR.396-398.44

Paper Titles

Effect of Metal Ions (Cu²⁺/Fe²⁺) on the Antioxidant Activity of L-Ascorbic Acid-Glycine Model System
p.28

Study on the Pretreatment of Seawater to Reduce Turbidity and Boron Using Different Alkalizer
p.32

Synthesis and Characterization of a New Type of Smart Hydroxyapatite-PNIPAM Hybrid Nanopatrticles
p.35

Information-Entropy-Based Integrated Model for Predicting Burn-Through Point in Lead-Zinc Sintering Process
p.40

Extraction of Feature Photoacoustic Spectroscopy Probed by a Sensor against a Large Background Noise
p.44

Zinc and Cobalt Recovery from Co-Ni Residue of Zinc Hydrometallurgy by an Ammonia Process
p.48

Studies on the Antioxidant Activities of Total Alkaloids from the Fruits of Evodia rutaecarpa (Juss.) Benth
p.52

Investigation on the Synthesize Reaction Possibility of M(CO)₂CY-Ph₃XR(M=Cr, Mn; X=Sn, Ge; Y=S, Se; R= N(C₄H₄), N(C₈H₆), C₆H₅)
p.56

The Consequence Analysis of Pressure Vessel Failure
p.66

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 396-398Extraction of Feature Photoacoustic Spectroscopy...

Extraction of Feature Photoacoustic Spectroscopy Probed by a Sensor against a Large Background Noise

Abstract:

An algorithm of independent component analysis from blind source separation domain is used and a Δλ-model strong-noise immunity is proposed in this work. The test results showed that maximal extraction error is respectively 0.28% and 3.7% under a SNR of 1/886 and an excellent agreementbetween the numerical simulation and the actual detection value is found, and the detection limit of test sample is improved from 16 ppb with the model based on common linear equations to 2 ppb using the proposed model.