A rapid and high-performance sensor for lard adulterant in edible oil was developed using the tapered plastic optical fiber (POF) coated with graphene and multi-walled carbon nanotubes. The coating material was deposited onto a tapered POF with a taper waist diameter and a taper length of 0.45 mm and 1 cm, respectively. The addition of the coating material was used to increase the sensitivity and selectivity coefficient of the tapered POF toward the lard substance. The sensing mechanism is based on a simultaneous interaction of lard substance and an evanescent wave of tapered POF with the coating layers. The results showed that graphene coating on the tapered POF increased the selectivity coefficient of the tapered POF towards lard substance from 33.54 to 324.19, and it gave a sensitivity of 0.427 dBm/%. In comparison, multi-walled carbon nanotubes coating increased the selectivity coefficient to 71.65 and increased its sensitivity to 1.189dBm/%. Thus, the proposed configuration of the tapered POF with the coating material offered a simple configuration for a rapid, high sensitivity and selectivity detection of lard adulterant in edible oils.
The deformation and reconstruction of the composite propeller under the static load in the laboratory is studied so as to provide the basic research for the deformation and reconstruction of the underwater deformed propeller. The fiber Bragg grating (FBG) sensor is proposed to be used for strain monitoring and deformation reconstruction of the carbon fiber reinforced polymer (CFRP) propeller, and a reconstruction algorithm of structural curvature deformation of the CFRP propeller based on strain information is presented. The reconstruction algorithm is verified by using variable-thickness CFRP laminates in the finite element software. The results show that the relative error of the reconstruction algorithm is within 8%. Then, an experimental system of strain monitoring and deformation reconstruction for the CFRP propeller based on the FBG sensor network is built. The propeller blade is loaded in the form of the cantilever beam, and the blade deformation is reconstructed by the strain measured by the FBG sensor network. Compared with the blade deformation measured by three coordinate scanners, the reconstruction relative error is within 15%.
The detection and reconstruction of transparent objects have remained challenging due to the absence of their features and variations in the local features with variations in illumination. In this paper, both compressive sensing (CS) and super-resolution convolutional neural network (SRCNN) techniques are combined to capture transparent objects. With the proposed method, the transparent object’s details are extracted accurately using a single pixel detector during the surface reconstruction. The resultant images obtained from the experimental setup are low in quality due to speckles and deformations on the object. However, the implemented SRCNN algorithm has obviated the mentioned drawbacks and reconstructed images visually plausibly. The developed algorithm locates the deformities in the resultant images and improves the image quality. Additionally, the inclusion of compressive sensing minimizes the measurements required for reconstruction, thereby reducing image post-processing and hardware requirements during network training. The result obtained indicates that the visual quality of the reconstructed images has increased from a structural similarity index (SSIM) value of 0.2 to 0.53. In this work, we demonstrate the efficiency of the proposed method in imaging and reconstructing transparent objects with the application of a compressive single pixel imaging technique and improving the image quality to a satisfactory level using the SRCNN algorithm.
Cascaded random Raman fiber lasers (CRRFLs) have been used as a new platform for designing high power and wavelength-agile laser sources. Recently, CRRFL pumped by ytterbium-doped random fiber laser (YRFL) has shown both high power output and low relative intensity noise (RIN). Here, by using a wavelength- and bandwidth-tunable point reflector in YRFL, we experimentally investigate the impacts of YRFL on the spectral and RIN properties of the CRRFL. We verify that the bandwidth of the point reflector in YRFL determines the bandwidth and temporal stability of YRFL. It is found that with an increase in the bandwidth of the point reflector in YRFL from 0.2nm to 1.4nm, CRRFL with higher spectral purity and lower RIN can be achieved due to better temporal stability of YRFL pump. By broadening the point reflector’s bandwidth to 1.4nm, the lasing power, spectral purity, and RIN of the 4th-order random lasing at 1349nm can reach 3.03W, 96.34%, and −115.19 dB/Hz, respectively. For comparison, the spectral purity and RIN of the 4th-order random lasing with the point reflector’s bandwidth of 0.2 nm are only 91.20% and −107.99dB/Hz, respectively. Also, we realize a wavelength widely tunable CRRFL pumped by a wavelength-tunable YRFL. This work provides a new platform for the development of ideal distributed Raman amplification pump sources based on CRRFLs with both good temporal stability and wide wavelength tunability, which is of great importance in applications of optical fiber communication and distributed sensing.
Long-period waveguide grating based filters have attracted attention due to their flexible fabrication, a variety of materials and structures, low back reflection, low insertion loss, and excellent performance in the tuning range and temperature sensitivity. To our knowledge, for the first time, a two-segment polymer long-period waveguide grating was cascaded to implement a filter with a narrower bandwidth. Experimental results showed that the device had a maximum extinction ratio of 24 dB at 1 577 nm, and the 12 dB bandwidth was 10 nm. The temperature sensitivity of the fabricated device was 1.79 nm/°C.
The two-dimensional (2D) lidar is a ranging optical sensor that can measure the cross-section of the geometric structure of the environment. We propose a robust 2D lidar simultaneous localization and mapping (SLAM) algorithm working in ambiguous environments. To improve the front-end scan-matching module’s accuracy and robustness, we propose performing degeneration analysis, line landmark tracking, and environment coverage analysis. The max-clique selection and odometer verification are introduced to increase the stability of the SLAM algorithm in an ambiguous environment. Moreover, we propose a tightly coupled framework that integrates lidar, wheel odometer, and inertial measurement unit (IMU). The framework achieves the accurate mapping in large-scale environments using a factor graph to model the multi-sensor fusion SLAM problem. The experimental results demonstrate that the proposed method achieves a highly accurate front-end scan-matching module with an error of 3.8% of the existing method. And it can run stably in ambiguous environments where the existing method will be failed. Moreover, it ccan successfully construct a map with an area of more than 250 000 square meters.
Sulfamethoxazole (SMX) is a sulfonamide antibiotic primarily used to treat urinary tract infections and used in veterinary and industrialized husbandry to treat diseases and food additives. Like other antibiotics, SMX is considered as a pollutant in water and food that threaten local life. This study developed a surface plasmon resonance (SPR) sensor chip that is fast, highly selective, and reusable, and requires no pretreatment for detecting SMX. As a receptor, SMX imprinted methacrylic acid-2-hydroxyethyl methacrylate-ethylene glycol dimethacrylate polymer [poly(MAA-HEMA-EGDMA)] was used. The surface of the gold SPR chips was coated with a drop-casting method. The nanofilm coated chips were characterized by scanning electron microscopy (SEM), atomic force microscopy (AFM), ellipsometer, contact angle measurement, and Fourier-transform infrared spectrometry (FTIR). Imprinting factor (IF) was calculated as: ΔR[MIP(molecularly imprinted polymers)]/ΔR[NIP(non-imprinted)]=12/3.5=3.4. Limit of detection (LOD) and limit of quantification (LOQ) values were calculated with 3 s/m and 10 s/m methods, and the results were found to be 0.001 1 µg/L for LOD 0.003 4 µg/L for LOQ. Adsorption studies on both standard SMX solution and commercial milk samples were applied. Also, we investigated the developed chip’s reusability, storability, and selectivity with amoxicillin and cefalexin.
A length-matched micro Fabry-Perot (FP) interferometer is proposed for strain measurement under irradiation environment. Theoretical simulation shows that a well length-matched FP sensor can achieve a very low drift of the cavity length and strain sensitivity in irradiation environment. In experiment, such an FP cavity is realized by laser micromachining. It shows a low cavity length drift of −0.037 µm and a strain sensitivity deviation of 0.52%, respectively, under gamma irradiation. Meanwhile, the intensity of interference fringes is also stable. As a result, such a length-matched FP cavity is a very promising candidate for strain sensing in radiative environments.
A novel fiber-optic magnetic field sensor with high interrogation speed and resolution by using an etched fiber Bragg grating (FBG) in conjunction with a dual-loop optoelectronic oscillator (OEO) is proposed and experimentally demonstrated. A commercial FBG is firstly dipped into mixed hydrofluoric acid solution to remove the cladding layer and then is embedded with the magnetic fluid (MF) as a sensing element. The central wavelength reflected from the FBG is related to the overall time delay of the dual-loop OEO, which determines the oscillating frequency of the OEO. Therefore, the magnetic field can be estimated by measuring the oscillating frequency shift of OEO. The experimental results show that the oscillating frequency linearly increases with the increment of the magnetic field, achieving the sensitivity of 16.3 Hz/Oe with a R-square of 0.991 in the range of 5 mT–10 mT. In addition, the maximum error is within ±0.05 mT in the range of 7 mT–8 mT, which offers potentials in many fields where the high-precision magnetic field measurement is required.