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Personal safety in public places has become the primary demand of modern people's social life, and the detection of dangerous liquids is a key technology in the field of security inspection. The spectral drop analysis method is used to study the identification of flammable liquids in this paper. The spectral droplet analysis system is constructed with the fiber-capacitance drop sensor and spectrometer, and through the combination of signal processing circuit and the acquisition software, the experimental platform is designed. Experiments with typical liquid samples are completed and the three-dimensional fingerprints of the samples are obtained. And the characteristic values of liquid samples are extracted after data processing, the methods of rapid identification of flammable liquids based on spectral and drop fingerprint information are researched. With the spectral information, the characteristic wavelength points are selected to extract the characteristic parameters of the sample using the principal component analysis method. And the discriminant prediction models are established by distance discrimination, Bayes discriminant and Fisher discriminant. With the drop fingerprint data, the characteristic parameters are extracted with waveform analysis method, and then the extreme learning machine algorithm is used to build classification and identification model. The experimental results show that it is feasible to identify flammable liquids by spectral droplet analysis method.
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