Search Results (62)

In the plant kingdom, stress can significantly impact physiological and metabolic processes, leading to growth inhibition, developmental abnormalities, and even mortality. Current detection methods primarily focus on changes in gene expression or observable disease symptoms. However, these approaches are often resource-intensive, costly, and procedurally complex. To overcome these challenges, this study introduces an innovative molecular communication framework for plant stress monitoring. In this framework, plants that release biogenic volatile organic compounds serve as transmitters, receiving plants act as receivers, and the air serves as the propagation channel. The primary objective is to develop a real-time stress detection method by modulating stress types into distinct profiles of biogenic volatile organic compounds. These profiles are transmitted as chemical signals and are demodulated at the receiver. We analyzed the effects of distance, wind speed, and other factors on compound dispersion in the channel, validating the system through simulations and a molecular communication testbed. This research provides an innovative technical approach for real-time plant stress monitoring while establishing a theoretical foundation for enhancing crop management efficiency and advancing precision agriculture. Full article

Quickly detecting hydrogen leakage is crucial to provide early warning for taking emergency measures to avoid personnel casualties and explosion accidents in hydrogen energy fields. Here, a compact optical fiber hydrogen sensing system with high sensitivity and quick response rate is proposed in this work. A laser diode (LD) and two photodetectors (PD) are employed as light source and optical signal transformation devices, respectively. This sensing system employs single-mode optical fiber deposited with WO₃-PdPt-Pt nanocomposite film system as sensing element. Under irrigating power of 6 mW, the sensing probe exhibits an ultra-fast response to hydrogen concentrations of 4000 ppm and 10,000 ppm, with response times of 0.44 s and 0.34 s, respectively. In addition, detection limit of 3 ppm can be achieved by using this sensing system. The sensor also shows good repeatability during hydrogen exposure of 3~10,000 ppm, demonstrating its great potential application for hydrogen leakage in hydrogen energy facilities. Full article

Under the dual impetus of the “Dual Carbon” goals and the construction of smart grids, the development of new energy power infrastructure has been fully realized. The All-Fiber Optical Current Transformer (FOCT), leveraging its unique advantages, is in the process of supplanting traditional current transformers to become the core component of power system monitoring equipment. Currently, to achieve higher precision and stability in magnetic field or current detection, FOCT structures frequently incorporate active components such as Y-waveguides and phase modulators, and closed-loop feedback systems are often used in demodulation. This has led to issues of high cost, complex demodulation, and difficult maintenance, significantly hindering the further advancement of FOCTs. Addressing the problems of high cost and complex demodulation, this paper proposes a passive multiplexing structure that achieves time-domain multiplexing of pulsed sensing signals, designs a corresponding intensity demodulation algorithm, and applies this structure to FOCTs. This enables low-cost, simple-demodulation current sensing, which can also be utilized for magnetic field detection, showcasing vast application potential. Full article

Aiming at the issues of low sensitivity and poor resistance to temperature and vibration interference in traditional optical fiber current transformers, as well as the structural complexity of magnetostrictive material-coupled sensors, this paper integrates a high-sensitivity electrostrictive piezoelectric ceramic sensor with an FBG-FP cascaded fiber-optic sensor. This coupling significantly optimizes the sensor structure. By employing orthogonal intensity demodulation to enhance detection sensitivity, and adopting a multi-cycle waveform-averaging method to calculate the DC output light intensity, temperature calibration and compensation are achieved through the correlation between the DC output light intensity and operating points. Experimental results demonstrate that the designed sensor exhibits a detection bandwidth of 0–7 kHz, fully meeting the requirements for power-frequency current detection. Its current measurement range spans 0.15–42 mA, with a minimum measurable current as low as 150 μA. This study provides a compact, high-precision, highly scalable, and adaptable current detection solution for power systems, demonstrating significant engineering application value. Full article

The beam exchange is a classical supplementary technique for spatio-temporal modulation in a dual-beam setup. In order to save time, the reduced polarimetric-optical-switching (RPOS) technique was propsed as an alternative technique. In this work, we revisit the assumptions of several formulas specifically constructed for this technique and evaluate their validity in different modulation schemes (e.g., dependent modulation), especially when reference measurements are acquired using specific Stokes signals. Subsequently, we compare the RPOS technique based on the most appropriate formula with the demodulation method based on the demodulation matrix by using synthesized observation data. The artificial observation takes into account the influence several factors have on the modulated intensities, including dark current, gain variation, atmospheric seeing fluctuations, and photon noise. Our numerical tests demonstrate that the RPOS technique has an advantage in mitigating the effects of atmospheric seeing fluctuations and gain variations between two beams. However, the selection of a specific Stokes signal for reference measurements has a notable impact on performance in minimizing the effect of photon noise. Full article

In order to meet the reliability requirements of communication for underwater resource exploration, this study develops an underwater wireless optical communication (UWOC) system utilizing a blue semiconductor laser as the light source. At the receiver, a fully digital automatic gain control (AGC) module, implemented on a field-programmable gate array (FPGA), is designed to mitigate signal fluctuations induced by underwater turbulence. Digital filtering techniques, including median filtering (MF) and bilateral edge detection filtering (BEDF), are also employed to improve signal demodulation reliability. An improved Reed–Solomon (RS) coding scheme is further adopted to significantly reduce the bit error rate (BER). The design of a highly reliable UWOC system was realized based on the above techniques. The system’s performance was evaluated across a range of signal-to-noise ratios (SNRs) and bubble intensities. The results show that the digital AGC module can provide a gain range from −3.2 dB to 16 dB, adapting to varying signal strengths, which greatly bolsters the system’s resilience against underwater turbulence. Filtering techniques and RS coding further enhance the system’s immunity to interference and reduce the system BER. Communication experiments were conducted over various distances under three distinct water quality conditions. The results demonstrate that, within the detection range of the avalanche photodiode (APD), the system consistently maintained a BER below 3.8 × 10⁻³ across all water types, thereby confirming its high reliability. In clear seawater, the system demonstrated reliable information transmission over a 10 m distance at a data rate of 10 Mbps, achieving a BER of 2 × 10⁻⁸. Theoretical calculations indicate that the maximum transmission distance in clear seawater can reach 111.35 m. Full article

A novel approach to fibre Bragg grating spectra processing is proposed. The method is based on the use of nonlinear filtration and raising the spectrum value to the second power. A combination of geometric and arithmetic mean filtering is used as nonlinear filtration. The properties of the denoising method are presented on simulation data with different signal-to-noise ratios and on experimental data. The most advantageous combination is raising the intensity of the spectrum to the square power preceded by its significant smoothing. The centroid, fast phase correlation, and cross-correlation methods are used to determine the wavelength shift in the spectrum. To obtain experimental data, measurements of the FBG in reflection mode placed in a temperature chamber with the possibility of temperature control are obtained. The simulations, measurements, and their numerical analysis confirm the usefulness of the proposed methods for demodulating the wavelength shift of FBG spectra. Full article

The distributed feedback fiber (DFB) laser has been extensively researched for the purpose of detecting partial discharges in power equipment. DFB is demodulated using an unbalanced interferometer, which is not only structurally complex but also prone to introducing significant noise when the fiber distance is long. In order to address this issue, this paper presents the design of a low-noise demodulation system. The theoretical model of external optical feedback noise is described in this study. The relationship between this noise and the DFB linewidth is established by introducing the external optical feedback coefficient C. The theoretical results demonstrate that the system noise is minimized when C is approximately 30. A low-noise partial discharge detection system combined with a polarization optical demodulation method is developed. The experimental results confirmed the local discharge detection capability of the system in solid insulation and significantly reduced the system noise. This result promotes wider application and promotion of DFB lasers. Full article

Carbon fiber composites (CFRPs) are prone to impact loads during their production, transportation, and service life. These impacts can induce microscopic damage that is always undetectable to the naked eye, thereby posing a significant safety risk to the structural integrity of CFRP structures. In this study, we developed an impact localization system for CFRP structures using extrinsic Fabry–Perot interferometric (EFPI) sensors. The impact signals detected by EFPI sensors are demodulated at high speeds using an intensity modulation method. An impact localization method for the CFRP structure based on the energy–entropy ratio endpoint detection and CNN-BIGRU-Attention is proposed. The time difference of arrival (TDOA) between signals from different EFPI sensors is collected to characterize the impact location. The attention mechanism is integrated into the CNN-BIGRU model to enhance the significance of the TDOA of impact signals detected by proximal EFPI sensors. The model is trained using the training set, with its parameters optimized using the sand cat swarm optimization algorithm and validation set. The localization performance of different models is then evaluated and compared using the test set. The impact localization system based on the CNN-BIGRU-Attention model using EFPI sensors was validated on a CFRP plate with an experimental area of 400 mm × 400 mm. The average error in impact localization is 8.14 mm, and the experimental results demonstrate the effectiveness and satisfactory performance of the proposed method. Full article

To solve the problems of channel crosstalk and edge jitter caused by the Fourier transform demodulation of polarimetric-spectral intensity modulation in polarization spectral data, this paper proposes a Four-Channel Polarimetric Spectrometer (FCPS) with two groups of polarimetric-spectral intensity modulation (PSIM). FCPS can demodulate the full Stokes spectra information by system matrix calibration in the spatial domain. The traditional channel filtering method and the FCPS data demodulation method are simulated, and their results are compared. The simulated results show that the FCPS does not have the problem of the edge jitter, and the demodulation accuracy is higher. It is confirmed that the angle error of phase retarders has little influence on the data reconstruction, and the maximum allowable angle error of the calibration light linear polarizer cannot exceed 0.4°. Full article

Generative adversarial networks (GANs) are widely used in image conversion tasks and have shown unique advantages in the context of face image beautification, as they can generate high-resolution face images. When used alongside potential spatial adjustments, it becomes possible to control the diversity of the generated images and learn from small amounts of labeled data or unsupervised data, thus reducing the costs associated with data acquisition and labeling. At present, there are some problems in terms of face image beautification processes, such as poor learning of the details of a beautification style, the use of only one beautification effect, and distortions being present in the generated face image. Therefore, this study proposes the facial image beautification generative adversarial network (FIBGAN) method, in which images with different beautification style intensities are generated with respect to an input face image. First, a feature pyramid network is used to construct a pre-encoder to generate multi-layer feature vectors containing the details of the face image, such that it can learn the beautification details of the face images during the beautification style transmission. Second, the pre-encoder combines the separate style vectors generated with respect to the original image and the style image to transfer the beautification style, such that the generated images have different beautification style intensities. Finally, the weight demodulation method is used as the beautification style transmission module in the generator, and the normalization operation on the feature map is replaced with the convolution weight to eliminate any artifacts from the feature map and reduce distortions in the generated images. The experimental results show that the FIBGAN model not only transmits the beautification style to face images in a detailed manner but also generates face images with different beautification intensities while reducing the distortion of the generated face images. Therefore, it can be widely used in the beauty and fashion industry, advertising, and media production. Full article

Assessing the internal quality of fruits is crucial in food chemistry and quality control, and bruises on peaches can affect their edible value and storage life. However, the early detection of slight bruises in yellow peaches is a major challenge, as the symptoms of slight bruises are difficult to distinguish. Herein, this study aims to develop a more simple and efficient structured-illumination reflectance imaging system (SIRI) and algorithms for the early nondestructive detection of slight bruises in yellow peaches. Pattern images of samples were acquired at spatial frequencies of 0.05, 0.10, 0.15, and 0.20 cycle ${mm}^{-1}$ and wavelengths of 700, 750, and 800 nm using a laboratory-built multispectral structured-illumination reflectance imaging system (M-SIRI), and the direct component (DC) and alternating component (AC) images were obtained by image demodulation. A spatial frequency of 0.10 cycle ${mm}^{-1}$ and wavelength of 700 nm were determined to be optimal for acquiring pattern images based on the analysis of the pixel intensity curve of the AC image; then, the pattern images of all yellow peaches samples were obtained. The ratio image (RT) between the AC image and the DC image significantly enhances bruise features. An improved Otsu algorithm is proposed to improve the robustness and accuracy of the Otsu algorithm against dark spot noise in AC and RT images. As a comparison, the global thresholding method and the Otsu method were also applied to the segmentation of the bruised region in all samples. The results indicate that the I-Otsu algorithm has the best segmentation performance for RT images, with an overall detection accuracy of 96%. This study demonstrates that M-SIRI technology combined with the I-Otsu algorithms has considerable potential in non-destructive detection of early bruises in yellow peaches. Full article

This paper presents the design of a strain-sensitive, dual ball-shaped tunable zone (DBT) taper structure for light intensity modulation. Unlike conventional tapered optical fibers, the DBT incorporates a central light field modulation zone within the taper. By precisely controlling the fusion parameters between single-mode fiber (SMF) and polarization-maintaining fiber (PMF), the ellipticity of the modulation zone can be finely adjusted, thereby optimizing spectral characteristics. Theoretical analysis based on polarization mode interference (PMI) coupling confirms that the DBT structure achieves a more uniform spectral response. In cantilever beam strain tests, the DBT exhibits high sensitivity and a highly linear intensity–strain response (R² = 0.99), with orthogonal linear polarization mode interference yielding sensitivities of 0.049 dB/με and 0.023 dB/με over the 0–244.33 με strain range. Leveraging the DBT’s light intensity sensitivity, a temperature-compensated intensity difference and ratio calculation method is proposed, effectively minimizing the influence of light source fluctuations on sensor performance and enabling high-precision strain measurements with errors as low as ±6 με under minor temperature variations. The DBT fiber device, combined with this innovative demodulation technique, is particularly suitable for precision optical sensing applications. The DBT structure, combined with the novel demodulation method, is particularly well-suited for high-precision and stable measurements in industrial monitoring, aerospace, civil engineering, and precision instruments for micro-deformation sensing. Full article

The deep integration of communication and sensing technology in fiber-optic systems has been highly sought after in recent years, with the aim of rapid and cost-effective large-scale upgrading of existing communication cables in order to monitor ocean activities. As a proof-of-concept demonstration, a high-degree of compatibility was shown between forward-transmission distributed fiber-optic vibration sensing and an on–off keying (OOK)-based communication system. This type of deep integration allows distributed sensing to utilize the optical fiber communication cable, wavelength channel, optical signal and demodulation receiver. The addition of distributed sensing functionality does not have an impact on the communication performance, as sensing involves no hardware changes and does not occupy any bandwidth; instead, it non-intrusively analyzes inherent vibration-induced noise in the data transmitted. Likewise, the transmission of communication data does not affect the sensing performance. For data transmission, 150 Mb/s was demonstrated with a BER of 2.8 × 10⁻⁷ and a Q_dB of 14.1. For vibration sensing, the forward-transmission method offers distance, time, frequency, intensity and phase-resolved monitoring. The limit of detection (LoD) is 8.3 pε/Hz^1/2 at 1 kHz. The single-span sensing distance is 101.3 km (no optical amplification), with a spatial resolution of 0.08 m, and positioning accuracy can be as low as 10.1 m. No data averaging was performed during signal processing. The vibration frequency range tested is 10–1000 Hz. Full article

Fiber-optic sensors, such as fiber Bragg grating (FBG) sensors and fiber-optic interferometers, have excellent sensing capabilities for industrial, chemical, and biomedical engineering applications. This paper used machine learning to enhance the number of fiber-optic sensing placement points and promote the cost-effectiveness and diversity of fiber-optic sensing applications. In this paper, the framework adopted is the FBG cascading an interferometer, and a deep belief network (DBN) is used to demodulate the wavelength of the sampled complex spectrum. As the capacity of the fiber-optic sensor arrangement is optimized, the peak spectra from FBGs undergoing strain or temperature changes may overlap. In addition, overlapping FBG spectra with interferometer spectra results in periodic modulation of the spectral intensity, making the spectral intensity variation more complex as a function of different strains or temperature levels. Therefore, it may not be possible to analyze the sensed results of FBGs with the naked eye, and it would be ideal to use machine learning to demodulate the sensed results of FBGs and the interferometer. Experimental results show that DBN can successfully interpret the wavelengths of individual FBG peaks, and peaks of the interferometer spectrum, from the overlapping spectrum of peak-overlapping FBGs and the interferometer. Full article