Abstract
Tunable diode laser absorption spectroscopy technology (TDLAS) has been widely applied in gaseous component analysis based on gas molecular absorption spectroscopy. When dealing with molecular absorption signals, the desired signal is usually interfered by various noises from electronic components and optical paths. This paper introduces TDLAS-specific signal processing issues and summarizes effective algorithms so solve these.
Highlights
Sensors based on Tunable Diode Laser Absorption Spectroscopy (TDLAS) have the advantages of high sensitivity, high stability, high selectivity and fast response, and have been widely applied in atmospheric environmental monitoring [1,2,3], medical health [4], industrial production [5,6], military surveying [7,8] and other fields
Many kinds of algorithms have been developed to denoise from different perspectives, examples of which are the linear filters based on early filtering theory, such as the Wiener filter and Kalman filter [54,55]; the fitting algorithms based on nonlinear regression, such as least-squares method; and some other decomposition algorithms based on signal decomposition and reconstruction, such as empirical mode decomposition [49]
We mainly introduce the studies of wavelet transform (WT) to subjectivity deal with the of low-signal-to-noise ratio (SNR)
Summary
Sensors based on Tunable Diode Laser Absorption Spectroscopy (TDLAS) have the advantages of high sensitivity, high stability, high selectivity and fast response, and have been widely applied in atmospheric environmental monitoring [1,2,3], medical health [4], industrial production [5,6], military surveying [7,8] and other fields. In the development of TDLAS, many methods have been proposed to improve system accuracy and to measure resolution [17,18,19,20,21,22], which can be divided into two classes: software processing and hardware-based processing. With the continuous evolution of data processing technology, many data analysis algorithms have emerged in some fields [27,28] Some of these methods have been introduced and applied in TDLAS systems to enhance the accuracy and resolution performance. The first three paths [36,37] and mechanical jamming when the device is used Among these errors, the first three interferences are universal, and this article mainly introduces research works on these three issues. TDLAS systems systemsto to process signals with low SNR, including wavelet transform (WT).
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