A damage identification system of carbon fiber reinforced plastics (CFRP) structures is investigated using fiber Bragg grating (FBG) sensors and back propagation (BP) neural network. FBG sensors are applied to construct the sensing network to detect the structural dynamic response signals generated by active actuation. The damage identification model is built based on the BP neural network. The dynamic signal characteristics extracted by the Fourier transform are the inputs, and the damage states are the outputs of the model. Besides, damages are simulated by placing lumped masses with different weights instead of inducing real damages, which is confirmed to be feasible by finite element analysis (FEA). At last, the damage identification system is verified on a CFRP plate with 300 mm × 300 mm experimental area, with the accurate identification of varied damage states. The system provides a practical way for CFRP structural damage identification.

Diffraction gratings have been widely used in wavelength-controlled non-mechanical laser beam steering for high data-rate indoor optical wireless communications (OWC). Existing free-space diffraction gratings suffer from inherent difficulties of limited diffraction efficiency, bulky configuration, high cost and significant coupling loss with optical fiber links. In this work, a new optical approach for highly efficient, compact and fiber compatible laser beam steering using an in-fiber diffraction grating is proposed and experimentally demonstrated for the first time to our best knowledge. In-fiber diffraction is made possible based on a 45° tilted fiber grating (TFG), where wavelength dependent lateral scattering is obtained due to the strongly tilted grating structure. Improved diffraction efficiency of 93.5% has been achieved. In addition, the 45° TFG works perfectly for both light emission and reception, enabling full-duplex optical wireless transmission. Utility of the 45° TFG in all-fiber laser beam steering for multi-user full duplex optical wireless communications has been verified in experiments. 1.4 m free-space full-duplex wireless transmission has been demonstrated with data rate up to 12 Gb/s per beam using 2.4 GHz bandwidth OFDM signals.

This work reports a refractive index sensor made of plastic optical fiber (POF) with tapered structure. Transmission loss is measured when the external environment’s refractive index changes from 1.33 to 1.41. Three wavelengths (532, 633, and 780 nm) are used to evaluate the sensitivity of the sensor, and results indicate that 633 nm is the best sensing wavelength due to the increased levels of sensitivity achieved at this wavelength. A biconical sensing structure is designed to enhance the sensitivity of the sensor. A sensitivity of $950\mathrm{\mu W}/\mathrm{RIU}$ at 633 nm is obtained for a biconical sensing structure when launched power is 1 mW. Due to its sensitivity to the refractive index and simple construction, POF with tapered structure has potential applications in the biosensing field.

This paper presents a method based on signal correlation to detect delamination defects of widely used carbon fiber reinforced plastic with high precision and a convenient process. The objective of it consists in distinguishing defect and non-defect signals and presenting the depth and size of defects by image. A necessary reference signal is generated from the non-defect area by using autocorrelation theory firstly. Through the correlation calculation results, the defect signal and non-defect signal are distinguished by using Euclidean distance. In order to get more accurate time-of-flight, cubic spline interpolation is introduced. In practical automatic ultrasonic A-scan signal processing, signal correlation provide a new way to avoid problems such as signal peak tracking and complex gate setting. Finally, the detection results of a carbon fiber laminate with artificial delamination through ultrasonic phased array C-scan acquired from Olympus OmniScan MX2 and this proposed algorithm are compared, which showing that this proposed algorithm performs well in defect shape presentation and location calculation. The experiment shows that the defect size error is less than 4%, the depth error less than 3%. Compared with ultrasonic C-scan method, this proposed method needs less inspector’s prior-knowledge, which can lead to advantages in automatic ultrasonic testing.

The in-situ observation is of great significance to the study of the growth mechanism and controllability of two-dimensional transition metal dichalcogenides (TMDCs). Here, the differential reflectance spectroscopy (DRS) was performed to monitor the growth of molybdenum disulfide (MoS₂) on a SiO₂/Si substrate prepared by chemical vapor deposition (CVD). A home-built in-situ DRS setup was applied to monitor the growth of MoS₂ in-situ. The formation and evolution of monolayer MoS₂ are revealed by differential reflectance (DR) spectra. The morphology, vibration mode, absorption characteristics and thickness of monolayer MoS₂ have been confirmed by optical microscopy, Raman spectroscopy, ex-situ DR spectra, and atomic force microscopy (AFM) respectively. The results demonstrated that DRS was a powerful tool for in-situ observations and has great potential for growth mechanism and controllability of TMDCs prepared by CVD. To the best of the authors’ knowledge, it was the first report in which the CVD growth of two-dimensional TMDCs has been investigated in-situ by reflectance spectroscopy.