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Tube internal erosion, which corresponds to its wall thinning process, is one of the major safety concerns for tubes. Many sensing technologies have been developed to detect a tube wall thinning process. Among them, fiber Bragg grating (FBG) sensors are the most popular ones due to their precise measurement properties. Most of the current works focus on how to design different types of FBG sensors according to certain physical laws and only test their sensors in controlled laboratory conditions. However, in practice, an industrial system usually suffers from harsh and dynamic environmental conditions, and FBG signals are affected by many unpredictable factors. Consequently, the FBG signals have more fluctuations and are polluted by noises. Hence, the signals no longer directly follow the assumed physical laws and their proposed thinning detection mechanisms no longer work. Targeting at this, this article develops a data-driven model for FBG signal feature extraction and tube wall thickness monitoring using data analytic techniques. In particular, we develop a spatiotemporal model to describe dynamic FBG signals and extract features related to thickness. By taking physical law as guideline, we trace the relationship between the extracted features and the tube wall thickness, based on which we construct an online statistical monitoring scheme for tube wall thinning process. We use both laboratory test and field trial experiment to demonstrate the efficacy and efficiency of the proposed scheme.

In data analytics and pattern recognition, feature selection is a critical task to provide a subset of features with minimum redundancy. This reduces the computation time as well as cost. In this manuscript, a correlation based feature selection approach based on a modified binary ant colony optimization algorithm (MBACO) is proposed. Combined with random forest regression, the proposed MBACO algorithm is customized for a drift compensation application. In this application, the ant road map is initialized to avoid the local optimum. The proposed method is compared with that of binary particle swarm optimization on a well-known UCI dataset. Experimental results show that the proposed method exhibits better performance over the binary particle swarm optimization based approach.

A simulation design was presented to optimise the model of long period grating based fibre devices. The simulation used a modified phase matching condition to better estimate the resonance wavelengths in the transmission profile. Experiments were conducted to verify the results obtained in the simulation. The experimental results matched closely with the simulations.

A flexible, streamline and lightweight optical fibre connector-less interface composed of composite materials has been developed. Light is coupled in and out of the interface via a fibre launch system. A fibre Bragg grating (FBG) is embedded into the composite structure in order to investigate the optical performance of the interface. It is shown that an optical connection is maintained between the interface and multimode fibre in the cyclic test.

We report a fiber optic vibration sensor developed from a Fiber Bragg Grating (FBG) sensor. Three FBG vibration sensors are constructed and subjected to drop test, vibration test and mock train-railway positioning test. All the Bragg wavelengths of the sensors, as well as the Fast Fourier Transform (FFT) graphs are recorded by a computer via an FBG interrogator. Two commercial FBG vibration sensors are also tested for comparison. The results show that the fabricated sensors are robust, pick up low frequency vibrations, and detect a mini train position on a railway simulation.

In this paper, we investigate and experimentally demonstrate the influences of distance between the silica core and the glycerin core of a selectively glycerin-infiltrated photonic crystal fiber (PCF) on the mode characteristics, as well as the temperature sensitivity. By comparing the simulation and experiment results of three single-void glycerin-infiltrated PCFs with the glycerin core being one period, two periods and three periods away from the silica core respectively, it reveals that the smaller distance between the silica core and the glycerin core does not affect the modes indices, but increases the intensities of modes in the glycerin core and thus enhances the temperature sensitivity. Consequently, the temperature sensitivity can be controlled and tuned by appropriately designing the structure parameters of glycerin-infiltrated PCF. Besides, the highest temperature sensitivity up to -3.06nm/°C is obtained in the experiment as the glycerin core is nearest to the silica core. This work provides insights into the design and optimization of the liquid-infiltrated PCF for sensing applications.

In this report, we carry out simulation and experimental investigations of directional coupler structures with different separations between the glycerin selectively infiltrated channel and silica core of a large mode area Photonic Crystal Fiber (PCF). We assess their coupling characteristics and the corresponding temperature sensing capabilities. The temperature sensitivities of the glycerin selectively infiltrated channel adjacent to the silica core and two periods away from the silica core are −3.115 nm/°C and −2.332 nm/°C respectively. The glycerin selectively infiltrated channel three periods away from the silica core displays −107.8 pm/°C, an order of magnitude less temperature sensitive. The simulation results agree with the experimental results that there is a strong correlation between the coupling strength of the glycerin selectively infiltrated channel and the silica core, affecting its temperature response. ASTAR (Agency for Sci., Tech. and Research, S’pore) Published version