Wavelength Modulation Spectroscopy Research Articles

FDM-assisted OA-CEAS system for simultaneous measurements of temperature, CO2, and CO in flames

A system based on off-axis cavity enhanced absorption spectroscopy (OA-CEAS) integrated with frequency division multiplexing (FDM)-assisted wavelength modulation spectroscopy (WMS) was developed for simultaneous measurements of temperature, CO2, and CO in flames by employing two distributed feedback (DFB) diode lasers at 2.0 µm and 2.3 µm. An integrated cavity with an open-path configuration was made up of two cavity mirrors with a reflectivity of 99.8 %, and an effective optical absorption path length of approximately 5.2 m was achieved within a 6 cm diameter flame region. A CO2 line pair at 4990.418 cm−1 and 4990.664 cm−1, along with a CO line at 4300.699 cm−1, were selected as the measurement targets. The system was initially calibrated in a heated static cell and subsequently tested in C2H4/air premixed flat flames for six different equivalence ratios. All concentrations measured by the 1f-normalized 2f signals were compared with the results obtained from both the direct absorption signals and simulations based on adiabatic chemical equilibrium calculations using Chemkin. Additionally, the measured temperatures were compared with the thermocouple readings. According to the measurements conducted at representative C2H4 flames with different equivalence ratios, the accuracies for the measurements of temperature, CO2 concentrations, and CO concentrations were ∼1.062 %, ∼1.082 %, and ∼1.052 %, respectively. All the measurements illustrate the potential of the system for combustion diagnosis.

Long-Tune Natural Logarithmic Wavelength Modulation Spectroscopy for Gas Sensing.

This article presents a gas sensing method based on long-tune natural logarithmic wavelength modulation spectroscopy (long-tune ln-WMS) and explores means to improve its accuracy. The long-tune spectrum can detect multiple gases with high precision. In ln-WMS, due to the natural logarithm algorithm, the harmonic magnitude which is related to gas concentration would not be affected by the light intensity fluctuations. However, the background signal of the harmonic will become strong and nonlinear in the long-tune spectrum. Three CO2 absorption lines and one H2O line near 2004 nm are applied to verify the proposed theory. The effects of light intensity, modulation depth, gas concentration, and phase shift on the harmonics are tested separately through both simulations and experiments. The results reveal that our proposed method can always keep the harmonics at their maximum which ensures high measurement precision. Moreover, the background signal only varies with the modulation depth, not the concentration and light intensity. Even the mechanical vibrations cannot disturb the harmonics, which enables the proposed method to be suitable for gas detection in harsh environments, especially for heavy dust and severe mechanical vibrations. The CO2 concentration detection results indicate that when the background is eliminated, the accuracy can be achieved with a relative error of below 0.5%, while the error would be greater than 5% with background presence. The proposed long-tune ln-WMS method is effective for trace gas detection (weak absorption) or over-modulation conditions and has potential applications in field inspection.

Interband cascade laser absorption sensor for sensitive measurement of hydrogen chloride in smoke-laden gases using wavelength modulation spectroscopy

A tunable interband cascade laser sensor, based on wavelength modulation absorption spectroscopy near 3.73 µm, was developed to measure hydrogen chloride gas concentration in smoke-laden environments associated with the overhaul stages of firefighting. Wavelength selection near 2678cm−1 targets the P(0,9) transition within the fundamental vibrational band of HCl, chosen for its absorption strength and isolation from CO2, H2O, and CH4, as well as proximity to absorption features of other toxicant gases of interest in firefighting applications. Both scanned-wavelength direct absorption with a Voigt lineshape-fitting routine and a wavelength modulation spectroscopy absorption method are employed to recover species concentration. The laser sensor is paired with a compact commercial off-the-shelf 1 m multipass optical gas cell modified to use polished Alloy 20 steel mirrors for increased corrosion resistance against humid and acidic gases, and it is tested by sampling effluent gases from pyrolyzing and burning solid samples of polyvinyl chloride under a radiant heating apparatus in a laboratory fume hood. The wavelength modulation spectroscopy method is demonstrated to enable measurement at the near-ppm-level within a compact form-factor and to provide insights into the thermochemical pyrolysis processes that lead to the formation of hydrogen chloride when polyvinyl chloride is exposed to radiant heating.

Empirical Modal Decomposition Combined with Deep Learning for Photoacoustic Spectroscopy Detection of Mixture Gas Concentrations.

In photoacoustic spectroscopy based multicomponent gas analysis, the overlap of the absorption spectra among different gases can affect the measurement accuracy of gas concentrations. We report a multicomponent gas analysis method based on empirical modal decomposition (EMD), convolutional neural networks (CNN), and long short-term memory (LSTM) networks that can extract the exact concentrations of mixed gases from the overlapping wavelength-modulated spectroscopy with second harmonic (WMS-2f) detection. The WMS-2f signals of 25 different concentration combinations of acetylene-ammonia mixtures are detected using a single distributed feedback laser (DFB) at 1531.5 nm. The acetylene concentrations range from 2.5 to 7.5 ppm and the ammonia concentrations from 12.5 to 37.5 ppm. The data set is enhanced by cyclic shifting and adding Gaussian noise. The classification accuracy of the test set reaches 99.89% after tuning. The mean absolute errors of the five additional sets of data measured under different conditions are 0.092 ppm for acetylene and 1.902 ppm for ammonia, within the above concentration ranges.

Cavity-enhanced Faraday rotation spectroscopy for interference-free measurement of OH radical at 2.8 μm

An instrument based on cavity-enhanced Faraday rotation spectroscopy (CE-FRS) operating at 2.8 μm has been developed for interference-free measurement of OH radicals in the laboratory. By off-axis coupling of a continuous-wave laser into a high finesse optical cavity, FRS signal is obtained from balanced detection of time-integrated light intensity leaking out of the cavity in the presence of magnetic field. Radio-frequency white noise (5–520 MHz) was injected into laser current which reduced intensity fluctuations in cavity transmission, thus improved the signal-to-noise ratio of the spectroscopic signal by a factor of 2. The setup provides a simple and robust spectroscopic instrument for in-situ and highly-selective detection of paramagnetic species. We demonstrated the instrument’s capabilities using OH radical with concentration in the range of 1012 molecule.cm−3, generated by microwave discharge of water vapor at low pressure. The CE-FRS instrument exhibited a limit of detection of ∼ 1010 molecule.cm−3 in an integration time of 20 s, which is enhanced by a factor of 2.5 compared to cavity-enhanced wavelength modulation spectroscopy involving an off-axis integrated cavity output spectroscopy approach. A time-resolved FRS signal was recorded in a pulsed microwave discharge regime, giving a millisecond time resolution for the measurement of OH concentration profile. The developed instrument provides a potential analytical tool for the measurement of OH concentration for chemical kinetic study in reactor cells.

Simultaneous measurement of carbon monoxide and carbon dioxide for combustion diagnosis using 2 μm laser absorption spectroscopy

AbstractCarbon monoxide (CO) and carbon dioxide (CO2) are products of incomplete combustion and complete combustion, respectively. Time‐resolved knowledge of CO and CO2 exhaust concentrations will aid in improving combustion strategies, control, and efficiency. To achieve online high‐precision simultaneous measurement of CO and CO2, a tunable diode laser absorption spectroscopy‐based sensor is designed and constructed. Two diode lasers with central wavelengths of 2.3 and 2.0 μm are multiplexed in time‐division to cover the absorption spectral lines of CO at 4285.00 cm−1 and CO2 at 4989.96 cm−1, respectively. Wavelength modulation spectroscopy with second harmonic detection normalized by the first harmonic (WMS‐2f/1f) is employed. A software lock‐in amplifier and inversion algorithm are implemented for data processing and concentration acquisition. The entire measurement system is based on the idea of a virtual instrument and is carried out using a high‐speed data acquisition card and a computer. Experimental verification demonstrates that the measurement accuracies of CO and CO2 were 2.47% and 2.56%, respectively, with a time resolution of 20 ms. Dynamic measurement experiments with an alcohol blast burner validate the feasibility of measuring CO and CO2 in actual combustion environments. The developed sensor demonstrates the potential for real‐time and in situ carbon emission measurement for combustion diagnosis.

A TDLAS gas detection method based on digital signal modulation

This research presents a novel TDLAS gas concentration detection method based on digital modulation. The method inherits the advantage of a simple system structure from Direct Absorption Spectroscopy, as well as the excellent sensitivity of Wavelength Modulation Spectroscopy. A low-frequency sawtooth wave is employed to drive the laser, resulting in a digital direct absorption spectrum signal. By constructing a cosine modulation sequence in the time domain and performing linear interpolation on the direct absorption spectrum, it successfully converts to a wavelength-modulated absorption spectrum and simultaneously generates a digital reference signal at double the frequency. Ultimately, phase-locked amplification technology can be used to calculate the amplitude of the second harmonic. Since both the modulation and reference signals are generated digitally, they ensure a strict frequency-doubling relationship and phase correlation, which not only reduces the complexity of the hardware system but also effectively minimizes system errors. Because digital technology generates both the modulation and reference signals, it ensures that they have the same phase and a strict frequency-doubling relationship. Experimental results demonstrate that, when fitted by a cubic polynomial, the second harmonic amplitude and the gas concentration have a correlation coefficient (R2) as high as 0.99999 and a root mean square error as low as 0.0011. This proves the method's great accuracy and reliability in practical applications.

Suppression of interference fringes in wavelength modulation spectroscopy based on convolutional neural networks

To mitigate interference fringes in wavelength modulated spectroscopy (WMS), we introduce a new filter based on convolutional neural networks (New CNNF). This filter effectively suppresses both high and low-frequency variations of interference fringes, including those with envelopes. In striving for comprehensive interference fringe suppression across the entire frequency spectrum, while accommodating diverse cavity length conditions, we confront the challenge of data sparsity. To address this, we introduce a pioneering methodology: finely segmenting the dataset through concentration column density normalization, thereby achieving notable noise reduction. Through the construction and training of the New CNNF model, it was found to exhibit superior performance compared to traditional filtering algorithms, particularly under low signal-to-noise ratio (SNR) conditions.Following processing with the novel convolutional neural network filters (New CNNF), the sample's signal-to-noise ratio (SNR) improved by 26.70 dB, increasing from the original −10.11 dB. When the etalon lengths were 2 cm and 100 cm, the goodness of fit between the predicted second harmonic signal amplitude by New CNNF and the corresponding label concentration reached 0.9995 and 0.9999, respectively. Experimental results demonstrate that New CNNF effectively suppresses high and low-frequency variations and enveloped interference fringes in the TDLAS-WMS system, thereby enhancing the accuracy and stability of methane concentration measurements. CH4 transitions at λ = 1.654 μm were selected to validate this approach. Our method shows promising application prospects and can be extended to the sensing of other gas molecules.

Simultaneous measurement of SO2 and CO2 for sulfur content detection in marine diesel fuel using QCL absorption spectroscopy

Simultaneous measurement of CO2 and SO2 in ship exhaust gases is a common method for assessing compliance with sulfur emission standards. This study develops a new ship exhaust gas analyzer using time-division multiplexing of two quantum cascade lasers for simultaneous detection of the two gas species. A digital circuit integrated with a dual-channel waveform generator and a lock-in amplifier is developed to implement wavelength modulation spectroscopy (WMS) scheme. To enhance the measurement accuracy of SO2 with broadband absorption feature, a novel WMS approach that combines first-harmonic and normalized second-harmonic detection is introduced. A Kalman filter algorithm is employed to further refine the measurement precision. Experimental results show a 30.76% increase in detection accuracy. With a 1 s time resolution, the sensitivities of 13.4 ppb for SO2 and 9.81 ppm for CO2 are achieved. The effectiveness of the prototype for sulfur content detection is demonstrated, aiding emission management of water transport emissions.

Cubic nonlinear scanning for improved TDLAS-based methane concentration detection

In this study, we developed and validated an improved tuning method for a nonlinear scanning laser diode in methane gas sensing, using wavelength modulation spectroscopy - tunable diode laser absorption spectroscopy (WMS-TDLAS). This approach combines cubic nonlinear scanning with high-frequency modulation to precisely target the methane absorption peak at 6046.96 cm−1. The method enhances absorption time, thus increasing system sensitivity and stability. Our results show that this nonlinear scanning, optimized for peak absorption, significantly improves the slope of the methane concentration relationship curve by 76.9%. It also reduces the standard deviation by 61.1% and the limit of detection by 60% compared to linear scanning. The limit of detection the system is 4.2 ppm, and the optimal integration time is 48s. This novel modulation strategy significantly enhances the WMS-TDLAS system's efficiency, offering significant benefits for various applications.

A nonparametric point-by-point method to measure time-dependent frequency in wavelength modulation spectroscopy

A nonparametric point-by-point (NPP) method is presented for high-accuracy measurement of the time-dependent frequency (laser frequency) in tunable laser absorption spectroscopy, crucial for ensuring ultimate measurement accuracy. In wavelength modulation spectroscopy in particular, the parametric methods in current use for time-dependent frequency measurement are insufficiently accurate and are difficult to apply to complex modulation scenarios. Based on a multi-scale viewpoint, point-by-point measurement of the frequency is realized by linear superposition of the frequency information mapped from the interferometric signal on a unit scale and on a local scale. Validation experiments indicate that the measurement accuracy of the proposed NPP method is three times that of the existing parametric methods, while effectively immunizing against non-ideal tuning effects. Additionally, the NPP method is suitable for use with arbitrarily complex modulations such as square wave modulation, for which parametric methods are inapplicable.

Dual-species sensor using time-division multiplexed laser absorption spectroscopy for hydrogen sulfide and carbon monoxide measurement in SF6 insulated equipment fault detection

To address the issues of high detection limits, long response times, and susceptibility to cross-interference in the detection of characteristic gases CO and H2S produced by SF6 electrical equipment failures, a dual-species laser sensor prototype for SF6 decomposition products in electrical equipment was developed based on tunable diode laser absorption spectroscopy (TDLAS). The absorption lines of 2334 nm and 1576 nm were selected for CO and H2S, respectively. The concentration inversion was performed using wavelength modulation spectroscopy (WMS) with first harmonic normalization of the second harmonic. The experimental results demonstrate that a rapid response time of ∼30 s is achieved and the sensor has detection accuracies of 0.59 % for CO and 2.09 % for H2S, with minimum detection limits of 0.46 ppb and 14.00 ppb, respectively. The dual-species laser sensor allows for convenient, rapid, and precise detection of CO and H2S, showing promising application prospects in electrical environment monitoring.

Simultaneous measurement of methane, propane and isobutane using a compact mid-infrared photoacoustic spectrophone

Hydrocarbon gas sensing is a challenging task using laser absorption spectroscopy due to the complex and broad structure of absorption lines. This application requires quick, accurate and highly sensitive detection of hydrocarbon gases concentrations. In this paper, a compact photoacoustic spectrophone was developed to simultaneously measure methane, propane and isobutane. This spectrophone uses wavelength modulation spectroscopy (WMS) with a single acoustic resonator and a single DFB laser emitting at 3368 nm, which greatly reduces the system complexity without using time-division multiplexing technology for multi-gas sensing. Due to the complex and broadband absorption of hydrocarbon gases, a novel signal processing method based on multilinear regression with Ridge regression (MLR-RG) is proposed to reduce the measurement error caused by the nonlinearity of spectra signal. For single gas measurement, the detection limits of methane, propane, and isobutane are determined to be 828 ppb, 419 ppb, and 619 ppb (SNR = 1, integration time = 20 s), respectively. For simultaneous multi-gas sensing in a gaseous mixture, the detection limits of propane and isobutane are determined to be 7 ppb, 68 ppb with an integration time of 860 s, 460 s, respectively. The measurement accuracy of propane and isobutane using MLR-RG is higher than that of ordinary least squares regression and partial least squares regression by 75% and 60%, respectively. The proposed algorithm based on MLR-RG provides a promising approach to process the broad overlapping absorption spectra for accurately retrieving hydrocarbon gases concentrations.

Piezoelectrically tunable, narrow linewidth photonic integrated extended-DBR lasers

Recent advancements in ultra-low-loss silicon nitride (Si3N4)-based photonic integrated circuits have surpassed fiber lasers in coherence and frequency agility. However, high manufacturing costs of DFB and precise control requirements, as required for self-injection locking, hinder widespread adoption. Reflective semiconductor optical amplifiers (RSOAs) provide a cost-effective alternative solution but have not yet achieved similar performance in coherence or frequency agility, as required for frequency modulated continuous wave (FMCW) LiDAR, laser locking in frequency metrology, or wavelength modulation spectroscopy for gas sensing. Here, we overcome this challenge and demonstrate an RSOA-based and frequency-agile fully hybrid integrated extended distributed Bragg reflector (E-DBR) laser with high-speed tuning, good linearity, high optical output power, and turn-key operability. It outperforms Vernier and self-injection locked lasers, which require up to five precise operating parameters and have limitations in continuous tuning and actuation bandwidth. We maintain a small footprint by utilizing an ultra-low-loss 200 nm thin Si3N4 platform with monolithically integrated piezoelectric actuators. We co-integrate the DBR with a compact ultra-low-loss spiral resonator to further reduce the intrinsic optical linewidth of the laser to the Hertz-level—on par with the noise of a fiber laser—via self-injection locking. The photonic integrated E-DBR lasers operate at 1550 nm and feature up to 25 mW fiber-coupled output power in the free-running and up to 10.5 mW output power in the self-injection locked state. The intrinsic linewidth is 2.5 kHz in the free-running state and as low as 3.8 Hz in the self-injection locked state. In addition, we demonstrate the suitability for FMCW LiDAR by showing laser frequency tuning over 1.0 GHz at up to 100 kHz triangular chirp rate with a nonlinearity of less than 0.6% without linearization by modulating a Bragg grating using monolithically integrated aluminum nitride (AlN) piezoactuators.

Ultra-low concentration detection of dissolved C2H2 in oil using fixed-frequency RF-assisted calibration-free wavelength modulation spectroscopy

The monitoring sensitivity of dissolved C2H2 in transformer oil is crucial to ensuring the safe operation of electric power systems. A highly sensitive sensor system based on fixed-frequency radio frequency assisted calibration-free wavelength modulation spectroscopy (FF-RF-WMS-2f/1f) for dissolved C2H2 in transformer oil was developed and evaluated. Lowering the headspace sampling pressure to 0.1 atm effectively increased the outgassing ratio and detection signal of dissolved C2H2, while also reducing background interference. By employing a novel fixed-frequency RF-assisted modulation technique, we effectively suppressed the amplitude and influence of optical fringes and improved the system’s linear fitting R-squared value for gas-phase concentration from 0.9997 to 0.9999. Furthermore, the minimum detection limit (MDL), as calculated by Allan deviation, was reduced from 8.58 ppb to 4.36 ppb, while the optimal integration time increased slightly from 62 s to 79 s. The equivalent MDL for dissolved C2H2 reached 0.9 ppb. The comparative experiments showed that the error was less than 0.2 ppm or 8 %, the relative standard deviations (RSDs) of continuous measurement were less than 3 %, and the RSD at ultra-low concentration was less than 8 %. The experiments verified the high sensitivity and accuracy of the sensor system, making it suitable for ultra-low concentration dissolved C2H2 detection in transformer insulating oil.

Real-time breath gas analysis of methane using a multipass cell-based near-infrared gas sensor.

We demonstrated a near-infrared exhaled breath sensor for real-time methane measurements by using tunable diode laser absorption spectroscopy (TDLAS), which can enable the noninvasive diagnosis of intestinal tract problems. The core component of the near-infrared TDLAS sensor is a two-mirror-based multipass cell with nine-circle patterns. An optical path length of 23.4 m was achieved in a volume of 233.3 cm3, which effectively improved the detection sensitivity and shortened the gas exchange time. The minimum detection limit was 0.37 ppm by applying wavelength modulation spectroscopy, which was 12.4 times greater than that of direct absorption spectroscopy. In addition, combined with wavelength modulation spectroscopy, the two-mirror-based multipass cell enabled sub-second gas exchange time of 0.6 s. Methane breath experiments were conducted with six volunteers, and the real-time measurement results and concentrations at the end of exhalation were analyzed. This study demonstrates that the developed sensor has high sensitivity, high selectivity, and fast response for breath methane measurements and has promising potential for noninvasive, real-time, and point-of-care disease diagnosis in clinical applications.

Adaptation of state-of-the-art neural network architectures to interference fringe reduction in absorption spectroscopy

State-of-the-art neural network architectures in image classification and natural language processing were applied to interference fringe reduction in absorption spectroscopy by interpreting the data structure accordingly. A model was designed for temporal interpolation of background spectra and a different model was created for gas concentration fitting. The networks were trained on experimental data provided by a wavelength modulation spectroscopy instrument and the best performing architectures were analyzed further to evaluate generalization performance, robustness and transferability. A BERT-styled fitter achieved the best performance on the validation set and reduced the mean squared error of fitted amplitude by 99.5%. However, analysis of the de-noising behavior showed large biases. A U-Net styled convolutional neural network reduced the mean squared error of the interpolation by 93.2%. Evaluation on a test set provided evidence that the combination of model interpolation and linear fitting was robust and the detection limit was improved by 52.4%. Transferring the trained interpolator model to a different spectrometer setup showed no chaotic out-of-distribution effects. Additional fine-tuning further increased the performance. Neural network architectures cannot be generally applied to all absorption spectroscopy tasks. However, given the right task and the data representation, robust performance increase is achievable.

Uncertainty quantification for high-temperature flame sensing using wavelength modulation spectroscopy

In this study, we explore the uncertainty of the wavelength modulation spectroscopy (WMS) technique applied to water profile measurement in a flat flame. The scanned WMS-2f/1f method is used to measure the water profile in a C2H4-O2-Ar flame, using an absorption transition line near 1391.7 nm. The Monte Carlo sampling method is used for the uncertainty quantification (UQ) analysis. The results show a non-negligible uncertainty on the water concentration with an uncertainty range from 10% to 30%, depending on the uncertainty level considered for the input parameters of the spectroscopic model. Further sensitivity analyses show that the lower state energy (E′′), the line strength, and the temperature are the most important uncertainty sources. When multiple transition lines are involved, the line strength value controls the overall influence of the other parameters associated with these specific lines. We also compared the uncertainty obtained when applying the direct absorption spectroscopy (DA) and WMS techniques for a similar flame configuration. Only a slight advantage is observed for the WMS.

Highly sensitive mid-infrared methane remote sensor using a deep neural network filter.

A novel mid-infrared methane remote sensor integrated on a movable platform based on a 3.291-µm interband cascade laser (ICL) and wavelength modulation spectroscopy (WMS) is proposed. A transmitting-receiving coaxial, visualized optical layout is employed to minimize laser energy loss. Using a hollow retro-reflector remotely deployed as a cooperative target, the atmospheric average methane concentration over a 100-meter optical range is measured with high sensitivity. A deep neural network (DNN) filter is used for second harmonic (2f) signal denoising to compensate for the performance shortcomings of conventional filtering. Allan deviation analysis indicated that after applying the DNN filter, the limit of detection (LOD) of methane was 86.62 ppb with an average time of 1 s, decreasing to 12.03 ppb with an average time of 229 s, which is a significant promotion compared to similar work reported. The high sensitivity and stability of the proposed sensor are shown through a 24-hour continuous monitoring experiment of atmospheric methane conducted outdoors, providing a new solution for high-sensitivity remote sensing of atmospheric methane.

Time-Efficient SNR Optimization of WMS-Based Gas Sensor Using a Genetic Algorithm.

This paper presents the description of the wavelength modulation spectroscopy (WMS) experiment, the parameters of which were established by use of the Artificial Intelligence (AI) algorithm. As a result, a significant improvement in the signal power to noise power ratio (SNR) was achieved, ranging from 1.6 to 6.5 times, depending on the harmonic. Typically, optimizing the operation conditions of WMS-based gas sensors is based on long-term simulations, complex mathematical model analysis, and iterative experimental trials. An innovative approach based on a biological-inspired genetic algorithm (GA) and custom-made electronics for laser control is proposed. The experimental setup was equipped with a 31.23 m Heriott multipass cell, software lock-in, and algorithms to control the modulation process of the quantum cascade laser (QCL) operating in the long-wavelength-infrared (LWIR) spectral range. The research results show that the applied evolutionary approach can efficiently and precisely explore a wide range of WMS parameter combinations, enabling researchers to dramatically reduce the time needed to identify optimal settings. It took only 300 s to test approximately 1.39 × 1032 combinations of parameters for key system components. Moreover, because the system is able to check all possible component settings, it is possible to unquestionably determine the operating conditions of WMS-based gas sensors for which the limit of detection (LOD) is the most favorable.