近红外光谱分析方法研究:从传统数据到大数据
摘要
Near-infrared spectroscopy has been widely used in analytical sciences because of its speed, accuracy, environmental friendliness and simplicity. The data type associated with near-infrared spectra is becoming big data because of the development of the process in many fields. The methods used for processing of near-infrared spectra, including spectral preprocessing, outlier detection, multivariate calibration, modeling transfer, and their applications are summarized in this paper. The research approaches for big data analysis of near-infrared spectra, including online detection of industrial products, the identification of products from different batches, and the web of things constructed using near-infrared spectra, are also introduced. Additionally, the prospects for further development of the big data of near-infrared spectra and the cloud platform for near-infrared spectra are discussed.