Detection And Recognition Of Volatile Substances In Mothballs Using Laser-Induced Breakdown Spectroscopy And Raman Spectroscopy

Abstract

Mothballs are widely used in daily life as an air freshener, but their main components are volatile organic compounds that are harmful to the human body. A system combining laser-induced breakdown spectroscopy (LIBS) with Raman spectroscopy was built for the detection and recognition of volatile substances in mothballs in indoor environments. LIBS is employed for the online in-situ detection of volatile substances in two kinds of mothballs and to find their characteristic spectral lines. A machine learning model is then established to analyze the spectra of air and volatile substance in synthetic mothballs and natural camphor. The model based on principal component analysis and support vector classification achieved a recognition accuracy of 98.33%, indicating that LIBS has significant potential for recognizing volatile substances in mothballs when airborne. By comparing the experimental Raman spectra of mothballs and theoretical Raman spectra of their main components, the spectral fingerprints of mothballs are obtained as a supplement to LIBS detection.