Active noise reduction for a differential Helmholtz photoacoustic sensor excited by an intensity-modulated light source

Gas concentration prediction in photoacoustic spectroscopy using PSO-EAP-CNN to address correlation degradation

Photoacoustic spectroscopy (PAS) gas detection is frequently compromised by noise-induced correlation degradation, which significantly impacts measurement accuracy. To mitigate this issue, an advanced convolutional neural network (CNN) architecture, termed PSO-EAP-CNN, is proposed, which combines particle swarm optimization (PSO) with an ensemble augmented prediction (EAP) strategy. The proposed framework employs a multi-scale feature extraction mechanism through its convolutional architecture, while simultaneously optimizing network parameters via PSO, thereby achieving accelerated convergence and improved prediction stability. The incorporation of the EAP strategy further enhances the model's robustness and generalization ability under noisy conditions. Experimental results demonstrate significant improvements: compared to baseline CNN, PSO-EAP-CNN reduces MAE by 43.76 %, RMSE by 39.25 %, and MAPE by 51.15 %; compared to ordinary least squares regression, improvements reach 68.55 %, 67.43 %, and 75.21 % respectively. The model runs in only 10 seconds per execution. This work advances PAS-based gas detection, offering enhanced accuracy and noise resilience for practical trace gas analysis.

Fiber-Optic Sensor Spectrum Noise Reduction Based on a Generative Adversarial Network

In the field of fiber-optic sensing, effectively reducing the noise of sensing spectra and achieving a high signal-to-noise ratio (SNR) has consistently been a focal point of research. This study proposes a deep-learning-based denoising method for fiber-optic sensors, which involves pre-processing the sensor spectrum into a 2D image and training with a cycle-consistent generative adversarial network (Cycle-GAN) model. The pre-trained algorithm demonstrates the ability to effectively denoise various spectrum types and noise profiles. This study evaluates the denoising performance of simulated spectra obtained from four different types of fiber-optic sensors: fiber Fabry-Perot interferometer (FPI), regular fiber Bragg grating (FBG), chirped FBG, and FBG pair. Compared to traditional denoising algorithms such as wavelet transform (WT) and empirical mode decomposition (EMD), the proposed method achieves an SNR improvement of up to 13.71 dB, an RMSE that is up to three times smaller, and a minimum correlation coefficient (R2) of no less than 99.70% with the original high-SNR signals. Additionally, the proposed algorithm was tested for multimode noise reduction, demonstrating an excellent linearity in temperature response with a R2 of 99.95% for its linear fitting and 99.74% for the temperature response obtained from single-mode fiber sensors. The proposed denoising approach effectively reduces the impact of various noises from the sensing system, enhancing the practicality of fiber-optic sensing, especially for specialized fiber applications in research and industrial domains.

High-sensitivity trace gas detection based on differential Helmholtz photoacoustic cell with dense spot pattern

A high-sensitivity photoacoustic spectroscopy (PAS) sensor based on differential Helmholtz photoacoustic cell (DHPAC) with dense spot pattern is reported in this paper for the first time. A multi-pass cell based on two concave mirrors was designed to achieve a dense spot pattern, which realized 212 times excitation of incident laser. A finite element analysis was utilized to simulate the sound field distribution and frequency response of the designed DHPAC. An erbium-doped fiber amplifier (EDFA) was employed to amplify the output optical power of the laser to achieve strong excitation. In order to assess the designed sensor's performance, an acetylene (C2H2) detection system was established using a near infrared diode laser with a central wavelength 1530.3 nm. According to experimental results, the differential characteristics of DHPAC was verified. Compared to the sensor without dense spot pattern, the photoacoustic signal with dense spot pattern had a 44.73 times improvement. The minimum detection limit (MDL) of the designed C2H2-PAS sensor can be improved to 5 ppb when the average time of the sensor system is 200 s.

Highly sensitive photoacoustic gas sensor based on near-concentric cavity

The precise detection of trace gases in the atmosphere is vital for both environmental preservation and human health. Addressing the inherent challenges in enhancing the sensitivity of photoacoustic spectroscopy, a highly sensitive photoacoustic gas detection method utilizing a near-concentric cavity was proposed. By constructing a near-concentric optical cavity, laser reflections within the photoacoustic cell were substantially amplified, resulting in enhanced sensitivity of photoacoustic signal detection. Additionally, to align with the optical path characteristics of the near-concentric cavity, a miniaturized dumbbell-like photoacoustic cell was designed. Characterized by its high-frequency resonance, this design effectively mitigated background noise while maintaining a high sound pressure level. Experimental results demonstrated a remarkable enhancement in both signal intensity and signal-to-noise ratio by factors of 22.06 and 21.26, respectively, compared to traditional excitation methods. According to the 1σ standard, with a laser power of 21 mW, the setup achieved a detection limit of 10.15 ppb for NO2. The corresponding normalized noise equivalent absorption was calculated to be 2.84 × 10-9 cm-1WHz-1/2, with a gas consumption rate of merely 15.19 mL.

Simultaneous detection of greenhouse gases CH4 and CO2 based on a dual differential photoacoustic spectroscopy system

In addition to the atmospheric measurement, detection of dissolved carbon oxides and hydrocarbons in a water region is also an important aspect of greenhouse gas monitoring, such as CH4 and CO2. The first step of measuring dissolved gases is the separation process of water and gases. However, slow degassing efficiency is a big challenge which requires the gas detection technology itself with low gas consumption. Photoacoustic spectroscopy (PAS) is a good choice with advantages of high sensitivity, low gas consumption, and zero background, which has been rapidly developed in recent years and is expected to be applied in the field of dissolved gas detection. In this study, a miniaturized differential photoacoustic cell with a volume of 7.9 mL is designed for CH4 and CO2 detection, and a dual differential method with four microphones is proposed to enhance the photoacoustic signal. What we believe to be a new method increases photoacoustic signal by 4 times and improves the signal to noise ratio (SNR) over 10 times compared with the conventional single-microphone mode. Two distributed feedback (DFB) lasers at 1651 nm and 2004nm are employed to construct the PAS system for CH4 and CO2 detection respectively. Wavelength modulation spectroscopy (WMS) and 2nd harmonic demodulation techniques are applied to further improve the SNR. As a result, sensitivity of 0.44 ppm and 7.39 ppm for CH4 and CO2 are achieved respectively with an integration time of 10 s. Allan deviation analysis indicates that the sensitivity can be further improved to 42 ppb (NNEA=4.7×10-10cm-1WHz-1/2) for CH4 and 0.86 ppm (NNEA=5.3×10-10cm-1WHz-1/2) for CO2 when the integration time is extended to 1000 s.

Properties of a Symmetrical Photoacoustic Helmholtz Cell Operating with Imbalanced Counterphase Light Stimulation

The output signal from a photoacoustic cell based on a symmetrical Helmholtz resonator structure can be substantially increased if a counterphase light stimulation is applied to the cell cavities. However even slight differences in the intensity of the light beams irradiating the cavities may affect the frequency response of the cell and the output signal level. This paper shows the influence of the imbalanced light irradiation on the properties of such a cell. It was found that even at relatively high irradiation mismatch, and even with the photoacoustic signal detection implemented with a single microphone, the influence of the irradiation imbalance on the frequency response of the cell around the resonance frequency is not critical. In the case of differential detection of the photoacoustic signal, the imbalance of the light irradiation does not affect the frequency response of the cell, but only the output signal level.

Near-infrared sensitive differential Helmholtz-based hydrogen sulfide photoacoustic sensors

A near-infrared (NIR) sub-ppm level photoacoustic sensor for hydrogen sulfide (H₂S) using a differential Helmholtz resonator (DHR) as the photoacoustic cell (PAC) was presented. The core detection system was composed of a NIR diode laser with a center wavelength of 1578.13 nm, an Erbium-doped optical fiber amplifier (EDFA) with an output power of ∼120 mW, and a DHR. Finite element simulation software was used to analyze the influence of the DHR parameters on the resonant frequency and acoustic pressure distribution of the system. Through simulation and comparison, the volume of the DHR was 1/16 that of the conventional H-type PAC for a similar resonant frequency. The performance of the photoacoustic sensor was evaluated after optimizing the DHR structure and modulation frequency. The experimental results showed that the sensor had an excellent linear response to the gas concentration and the minimum detection limit (MDL) for H₂S detection in differential mode can reach 460.8 ppb.