Mathematical Methods and Algorithms for Improving Near-Infrared Tunable Diode-Laser Absorption Spectroscopy

Zhang, Tianyu; Kang, Jiawen; Meng, Dan; Wang, Hongwei; Mu, Zhengming; Zhou, Meng; Zhang, Xiaolin; Chen, Chen

doi:10.3390/s18124295

Cited by 35 publications

(23 citation statements)

References 71 publications

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“…Li et al summarized several commonly employed noise reduction schemes including signal averaging, modulation techniques, balanced detection, zero-background subtraction, and adaptive filtering [14]. Zhang et al focused on the various mathematical algorithms applied in TDLAS signal processing to enhance the accuracy and resolution of the sensor [15].…”

Section: Scope and Organization Of The Papermentioning

confidence: 99%

Laser Absorption Sensing Systems: Challenges, Modeling, and Design Optimization

Wang

Chao

2019

Applied Sciences

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Laser absorption spectroscopy (LAS) is a promising diagnostic method capable of providing high-bandwidth, species-specific sensing, and highly quantitative measurements. This review aims at providing general guidelines from the perspective of LAS sensor system design for realizing quantitative species diagnostics in combustion-related environments. A brief overview of representative detection limits and bandwidths achieved in different measurement scenarios is first provided to understand measurement needs and identify design targets. Different measurement schemes including direct absorption spectroscopy (DAS), wavelength modulation spectroscopy (WMS), and their variations are discussed and compared in terms of advantages and limitations. Based on the analysis of the major sources of noise including electronic, optical, and environmental noises, strategies of noise reduction and design optimization are categorized and compared. This addresses various means of laser control parameter optimization and data processing algorithms such as baseline extraction, in situ laser characterization, and wavelet analysis. There is still a large gap between the current sensor capabilities and the demands of combustion and engine diagnostic research. This calls for a profound understanding of the underlying fundamentals of a LAS sensing system in terms of optics, spectroscopy, and signal processing.

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Section: Scope and Organization Of The Papermentioning

confidence: 99%

Laser Absorption Sensing Systems: Challenges, Modeling, and Design Optimization

Wang

Chao

2019

Applied Sciences

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“…Sensors based on tunable diode laser absorption spectroscopy have the advantages of high sensitivity, high stability, high selectivity and fast response, and have been widely applied in atmospheric environmental monitoring. Zhang et al [ 10 ] have conducted a review and compared some effective algorithms using representative experiments to evaluate the performance both qualitatively and quantitatively.…”

Section: Contributionsmentioning

confidence: 99%

Sensor Signal and Information Processing II

Woo

Gao

2020

Sensors

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This Special Issue compiles a set of innovative developments on the use of sensor signals and information processing. In particular, these contributions report original studies on a wide variety of sensor signals including wireless communication, machinery, ultrasound, imaging, and internet data, and information processing methodologies such as deep learning, machine learning, compressive sensing, and variational Bayesian. All these devices have one point in common: These algorithms have incorporated some form of computational intelligence as part of their core framework in problem solving. They have the capacity to generalize and discover knowledge for themselves, learning to learn new information whenever unseen data are captured.

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“…However, conventional MPC usually requires the light beam to be incident in a specific angle to achieve an ideal optical length, which significantly increases the difficulty of optical alignment and reduces the stability of the sensor system due to the usage of plenty of optical elements. In addition, the presence of optical windows can also make the system susceptible to interference phenomena [33] . In order to address the above problems, a fiber-coupled MPC was introduced in this manuscript.…”

Section: Introductionmentioning

confidence: 99%

Sensitive carbon monoxide detection based on light-induced thermoelastic spectroscopy with a fiber-coupled multipass cell [Invited]

Liu

2022

Chin. Opt. Lett.

120

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A sensor based on light-induced thermoelastic spectroscopy (LITES) with a fiber-coupled multipass cell was demonstrated for carbon monoxide (CO) detection. The fiber-coupled structure has the merits of reducing optical interference and difficulty in optical alignment and increasing system robustness. A 1.57 μm continuous wave distributed feedback diode laser was used as the excitation source. A minimum detection limit of 9 ppm was obtained, and the calculated normalized noise equivalent absorption coefficient was 1.15 × 10 −7 cm −1 • W • Hz −1=2 . The reported CO-LITES sensor showed excellent linear concentration response and system stability.

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Mathematical Methods and Algorithms for Improving Near-Infrared Tunable Diode-Laser Absorption Spectroscopy

Cited by 35 publications

References 71 publications

Laser Absorption Sensing Systems: Challenges, Modeling, and Design Optimization

Laser Absorption Sensing Systems: Challenges, Modeling, and Design Optimization

Sensor Signal and Information Processing II

Sensitive carbon monoxide detection based on light-induced thermoelastic spectroscopy with a fiber-coupled multipass cell [Invited]

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