Simultaneous Detection of Multiple Atmospheric Components Using an NIR and MIR Laser Hybrid Gas Sensing System

Current Advances of CO Sensing Based on Low Dimensional Materials

Carbon monoxide (CO) is a harmful gas with significant impacts on human health and the environment. Its timely detection, especially in the event of thermal runaway in automotive lithium batteries, is crucial to prevent casualties. This paper reviews the progress in the development of efficient, sensitive, and reliable CO sensors, focusing on electrochemical, optical, and resistive sensing materials. Low-dimensional materials have a large specific surface area, providing an abundant number of active sites, which has drawn extensive attention from researchers. According to the different sensor signals, we categorized these sensors into electrical and optical signal sensors. We hope that by systematically introducing the sensing mechanism and sensing performance of these two kinds of sensors, appropriate CO sensors can be developed in different application scenarios so as to realize early warning and monitoring to the maximum extent, reduce industrial losses, and ensure the life and health of personnel.

Pressure-Compensated Fiber-Optic Photoacoustic Sensors for Trace SO2 Analysis in Gas Insulation Equipment

A high-sensitivity fiber-optic photoacoustic sensor with pressure compensation is proposed to analyze the decomposition component SO2 in high-pressure gas insulation equipment. The multiple influence mechanism of pressure on photoacoustic excitation and cantilever detection has been theoretically analyzed and verified. In the high-pressure environment, the excited photoacoustic signal is enhanced, which compensates for the loss of sensitivity of the cantilever. A fiber-optic F-P cantilever is utilized to simultaneously measure static pressure and dynamic photoacoustic wave, and a spectral demodulation method based on white light interference is applied to calculate the optical path difference of the F-P interferometer (FPI). The real-time pressure is judged through the linear relationship between the average optical path difference of FPI and the pressure, which gives the proposed fiber-optic photoacoustic sensor the inherent advantages of being uncharged and resistant to electromagnetic interference. The average optical path difference of FPI is positively related to pressure, with a responsivity of 0.6 μm/atm, which is based on changes in the refractive index of gas. In the range of 1-4 atm, the SO2 sensor has a higher detection sensitivity at high-pressure, which benefits from the pressure compensation effect. With the pressure environment of gas insulation equipment at 4 atm as the application background, the SO2 gas is tested. The detection limit is 20 ppb with an averaging time of 400 s.

Fiber-Optic Photoacoustic CO Sensor for Gas Insulation Equipment Monitoring Based on Cantilever Differential Lock-In Amplification and Optical Excitation Enhancement

A fiber-optic photoacoustic CO sensor for gas insulation equipment is proposed, which relies on F-P interferometric cantilever-based differential lock-in amplification and optical multipass excitation enhancement. The sensor has excellent characteristics of high sensitivity, antielectromagnetic interference, fast response, and long-distance detection. The photoacoustic pressure waves in the two resonators of the differential photoacoustic cell (DPAC) are simultaneously detected by two fiber-optic interferometric cantilevers and processed differentially; thereby, the gas flow noise is effectively suppressed. Based on the comprehensive analysis of the superposition of photoacoustic excitation and multipass absorption, the diameter of the resonator is determined to be 6 mm. The optical power emitted by the 1566.6 nm distributed feedback laser is increased to 500 mW by an erbium-doped fiber amplifier. The near-infrared light is reflected 30 times in the multipass cell, which improves the order of magnitude of optical effective excitation. Due to the low sound velocity of SF6 gas, the resonant frequency of the DPAC with a resonator length of 80 mm is 760 Hz. The response time to CO/SF6 gas is 93 s with a flow rate of 500 sccm. The detection limit of the CO sensor is 53 ppb, which realizes the accurate and timely perception of the SF6 decomposition derivative CO and provides technical support for trouble-free operation of gas insulation equipment.

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.

Ultrasensitive Online NO Sensor Based on a Distributed Parallel Self-Regulating Neural Network and Ultraviolet Differential Optical Absorption Spectroscopy for Exhaled Breath Diagnosis

The concentration of fractional exhaled nitric oxide (FeNO) is closely related to human respiratory inflammation, and the detection of its concentration plays a key role in aiding diagnosing inflammatory airway diseases. In this paper, we report a gas sensor system based on a distributed parallel self-regulating neural network (DPSRNN) model combined with ultraviolet differential optical absorption spectroscopy for detecting ppb-level FeNO concentrations. The noise signals in the spectrum are eliminated by discrete wavelet transform. The DPSRNN model is then built based on the separated multipeak characteristic absorption structure of the UV absorption spectrum of NO. Furthermore, a distributed parallel network structure is built based on each absorption feature region, which is given self-regulating weights and finally trained by a unified model structure. The final self-regulating weights obtained by the model indicate that each absorption feature region contributes a different weight to the concentration prediction. Compared with the regular convolutional neural network model structure, the proposed model has better performance by considering the effect of separated characteristic absorptions in the spectrum on the concentration and breaking the habit of bringing the spectrum as a whole into the model training in previous related studies. Lab-based results show that the sensor system can stably achieve high-precision detection of NO (2.59-750.66 ppb) with a mean absolute error of 0.17 ppb and a measurement accuracy of 0.84%, which is the best result to date. More interestingly, the proposed sensor system is capable of achieving high-precision online detection of FeNO, as confirmed by the exhaled breath analysis.

Ultrahigh Sensitive Trace Gas Sensing System with Dual Fiber-Optic Cantilever Multiplexing-Based Differential Photoacoustic Detection

An ultrahigh sensitive trace gas sensing system was presented with dual cantilever-based differential photoacoustic detection. By combining the double enhancement of multipass absorption and optical differential detection, the gas detection sensitivity was significantly improved. The dual-channel synchronous photoacoustic detection was realized by fiber-optic Fabry-Perot interference spectrum multiplexing. The photoacoustic signals detected by two fiber-optic cantilever microphones installed in a differential photoacoustic cell (DPAC) were out of phase, while the detected gas flow noises were in phase. The optical differential detection method achieved both highly sensitive optical interference measurement and differential noise suppression. In the multipass configuration, the interaction path between excitation light and target gas achieved 4.1 m, which improved the photoacoustic signal by an order of magnitude compared with a single reflection. The maximum gas flow allowed by the system based on the DPAC was 250 sccm, which realized the dynamic monitoring of H2S in the SF6 background. The detection limit for H2S in SF6 background was 5.1 ppb, which corresponds to the normalized noise equivalent absorption coefficient of 9 × 10-10 cm-1 W Hz-1/2.

Frequency division multiplexing and wavelength stabilized 2f/1f wavelength modulation spectroscopy for simultaneous trace CH4 and CO2 detection

A near-infrared (NIR) dual-gas sensor has been developed for simultaneous detection of atmospheric trace methane (CH4) and carbon dioxide (CO2). To realize high sensitivity and high precision, wavelength modulation spectroscopy with 2f/1f (WMS-2f/1f) detection method was adopted for eliminating laser light intensity fluctuation, and laser wavelength locking strategy based on a self-developed proportion integration differentiation (PID) algorithm was used for suppressing laser wavelength shifting effect. Two fiber-coupled DFB diode lasers with central wavelengths near 1653.7 nm and 1579.6 nm are applied for simultaneously measuring CH4 and CO2 spectra, respectively, and frequency division multiplexing (FDM) technique is employed to resolve the potential crosstalk effect. Real-time measurement of ambient atmospheric trace CH4 and CO2 was performed to demonstrate the long-term stability of the sensor system. Allan deviation analysis indicates that detection sensitivity of 0.1 ppm for CH4 and 2.27 ppm for CO2 was achieved with a 1 s average time, which can be further improved to 18 ppb and 0.3 ppm with the optimal integration time of 462 s and 392 s, respectively.

Method of adaptive wide dynamic range gas concentration detection based on optimized direct absorption spectroscopy

For wide dynamic range gas concentration detection based on tunable diode laser absorption spectroscopy (TDLAS), direct absorption spectroscopy (DAS) and wavelength modulation spectroscopy (WMS) are usually used in combination. However, in some application scenarios such as high-speed flow field detection, natural gas leakage, or industrial production, the requirements of wide-range, fast response and calibration-free must be met. Taking applicability and cost of TDALS-based sensor into consideration, a method of optimized direct absorption spectroscopy (ODAS) based on signal correlation and spectral reconstruction is developed in this paper. This method can achieve adaptive selection of the optimal benchmark spectrum for spectral reconstruction. Moreover, methane (CH₄) is taken as an example to carry out the experimental verification. Experimental results proved that the method satisfies wide dynamic range detection of more than 4 orders of magnitude. It is worth noting that when measuring large absorbance with concentration of 75 × 10⁴ppm with DAS and ODAS method, respectively, the maximum value of residual is reduced from 3.43 to 0.07. Furthermore, whether measuring gas of small or large absorbance with different concentrations, which vary from 100 ppm to 75 × 10⁴ppm, the correlation coefficient between standard concentrations and inverted concentrations is 0.997, showing the linear consistency of the method in wide dynamic range. In addition, the absolute error is 1.81 × 10⁴ppm when measuring large absorbance of 75 × 10⁴ppm. It greatly improves the accuracy and reliability with the new method. In summary, the ODAS method can not only fulfill the measurement of gas concentration in wide range, but also further expand the application prospects of TDLAS.

Multi-mechanism collaboration enhanced photoacoustic analyzer for trace H2S detection

To realize the real-time highly sensitive detection of SF₆ decomposition product H₂S, a multi-mechanism collaboration enhancement photoacoustic spectroscopy analyzer (MCEPA) based on acoustic resonance enhancement, cantilever enhancement and excitation light enhancement is proposed. An SF₆ background gas-induced photoacoustic cell (PAC) was used for acoustic resonance (AR) enhancement of the photoacoustic signals. A fiber-optic acoustic sensor based on a silicon cantilever is optimized and fabricated. The narrow-band acoustic signal enhancement based on cantilever mechanical resonance (MR) is realized in the optimal working frequency band of the PAC. A fiber-coupled DFB cascaded an Erbium-doped fiber amplifier (EDFA) realized the light power enhancement (LPE) of the photoacoustic signals excitation source. Experimental results show that the MR of the fiber-optic silicon cantilever acoustic sensor (FSCAS) is matched with the AR of the PAC and combined with the LPE, which realizes the multi-mechanism collaboration enhancement of weak photoacoustic signals. The Allan-Werle deviation evaluation showed that the minimum detection limit of H₂S in the SF₆ background is 10.96 ppb when the average time is 200 s. Benefiting from the all-optimization of photoacoustic excitation and detection, the MCEPA has near-field high-sensitivity gas detection capability immune to electromagnetic interference.

Development of a mid-infrared sensor system for early fire identification in cotton harvesting operations

To realize early fire identification in cotton harvesting operations, a mid-infrared carbon monoxide (CO) sensor system was developed. To match the broadband light source with a 15° divergence angle, a multipass gas cell (MPGC) with an effective path length of 180 cm was designed to improve sensor sensitivity, leading to a limit of detection (LoD) of 0.83 parts-per-million by volume (ppmv). A damping module with springs at the bottom and front/back sides was fabricated, which can effectively reduce the vibration intensity by >80%. The sensor system can operate normally from -40 °C to 85 °C by stabilizing the temperature of the optical module through heating or cooling as well as using automotive electronic components. An adaptive early fire identification algorithm based on a dual-parameter threshold alarming method was proposed to avoid false and missing alarms. Field deployments on a harvester verified the good practicability of the sensor system.

Frequency-Division-Multiplexed Multicomponent Gas Sensing with Photothermal Spectroscopy and a Single NIR/MIR Fiber-Optic Gas Cell

We report a multicomponent gas sensor based on hollow-core fiber (HCF) photothermal spectroscopy with frequency-division multiplexing (FDM). A single antiresonant HCF (AR-HCF) is used as the gas cell, which supports broadband transmission from near-infrared (NIR) to mid-infrared (MIR), covering the absorption lines of water vapor (H₂O) at 1.39 μm, carbon dioxide (CO₂) at 2.00 μm, and carbon monoxide (CO) at 4.60 μm. The NIR and MIR pump lasers at the above wavelengths are coupled into the AR-HCF from the opposite ends and modulated at 7.5, 8.0, and 8.5 kHz, respectively, to produce photothermal phase modulations at different frequencies. A common probe Fabry-Perot interferometer at 1.55 μm is adopted to detect the phase modulations, which are demodulated simultaneously using three lock-in amplifiers at the respective second harmonic frequencies. With a 13-cm-long AR-HCF, simultaneous detections of H₂O, CO₂, and CO are demonstrated with the limits of detection (LODs) of 2.7 ppm, 25 ppb, and 9 ppb for 1 s lock-in time constant, respectively. The LODs go down to 222, 1.5, and 0.6 ppb, respectively, for 1000 s averaging time. The photothermal signals of CO and CO₂, which are humidity-level dependent, are well calibrated by use of the measured H₂O signal. The multicomponent gas sensor is compact in configuration and shows good stability with signal fluctuation less than 1.7% over 2 h.

Vehicle-Deployed Off-Axis Integrated Cavity Output Spectroscopic CH4/C2H6 Sensor System for Mobile Inspection of Natural Gas Leakage

A vehicle-deployed parts-per-billion in volume (ppbv)-level off-axis integrated cavity output spectroscopic (OA-ICOS) CH₄/C₂H₆ sensor system was experimentally presented for mobile inspection of natural gas leakage in urban areas. For the time-division-multiplexing-based dual-gas sensor system, an antivibration 35-cm-long optical cavity with an effective path length of ∼2510 m was fabricated with a high-stability temperature and pressure control design. An Allan deviation analysis yielded a minimum detection limit of 0.2 ppbv for CH₄ detection and 10 ppbv for C₂H₆ detection for a 1 s averaging time. A natural gas leakage source location algorithm was proposed using an improved hybrid Nelder-Mead simplex search method and a particle swarm optimization (NM-PSO) algorithm. For field industrial application, the accuracy of the sensor system and leakage source location algorithm was confirmed through a CH₄/C₂H₆ cylinder leakage experiment on the campus. Furthermore, through natural gas pipeline network inspection measurements in urban areas, three types of leakage sources, including natural gas, biogas, and possible leakage source were respectively located and confirmed using the global positioning system and wind speed and direction measurement system, verifying the reliability and potential application of the vehicle-deployed inspection system for future natural gas pipeline leakage monitoring.

Dual-logarithmic demodulation method application in a wide gas optical thickness range

Direct absorption spectroscopy (DAS) is an extremely practical and effective technology to detect gas concentration in site applications. Dual-beam subtraction is one of the most common demodulation methods in DAS, yet this method cannot solve the problem of absolute absorption curve nonlinearization in a wide optical thickness range. A real-time and practical dual-logarithmic demodulation method is proposed and proved to be robust when the optical thickness is much greater than linear region. Moreover, the error of optical thickness peak is only 1.18% between the dual-logarithmic demodulation system and simulation after correcting the dual-beam subtraction demodulation system under a 300 K, 1 atm, and 3 m absorption path. When the range of optical thickness peak of acetylene is from 0.0252 to 2.5335 at 1532.83 nm, the peak voltages always maintain satisfactory linearity (R-square=0.9989).

Soil respiration analysis using a mid-infrared quantum cascade laser and calibration-free WMS-based dual-gas sensor

A high response and sensitive dual-gas sensor based on calibration-free wavelength modulation spectroscopy (CF-WMS) has been developed for the simultaneous detection of carbon monoxide (CO) and nitrous oxide (N2O) to eliminate the detection errors caused by light intensity variations. A multi-pass cell (MPC) was employed to lengthen the optical path to improve the precision of the sensing system by combining with a 4.56 μm mid-infrared quantum cascade laser (MIR-QCL). Meanwhile, a LabVIEW-based bi-molecular iterative fitting algorithm was used to infer the respective abundances of each species. The performance of the completed system was accurately evaluated with precisions of 3.4 ppb for CO and 3.8 ppb for N2O at a 1 s averaging time, which could be improved to 0.48 ppb for CO and 0.53 ppb for N2O at an averaging time of 154 s and 278 s, respectively. The grassland soil respiration analysis of CO and N2O was performed under different moisture conditions, which indicated that dried soil samples appeared to be a significant source of CO, while the sinks of CO and the sources of N2O occurred in the moist soil samples. The maximum exchange rates of the two gases were exhibited in moderate moisture soil samples rather than in the over-wet or arid soil samples. Moreover, a possible positive relationship between the sinks of CO and sources of N2O was established to illustrate the correlation of the two species in soil respiration.