Deep learning classification and regression models for temperature values on a simulated fibre specklegram sensor

Fiber optic specklegram sensors use the modal interference pattern (or specklegram) to determine the magnitude of a disturbance. The most used interrogation methods for these sensors have focused on point measurements of intensity or correlations between specklegrams, with limitations in sensitivity and useful measurement range. To investigate alternative methods of specklegram interrogation that improve the performance of the fiber specklegram sensors, we implemented and compared two deep learning models: a classification model and a regression model. To test and train the models, we use physical-optical models and simulations by the finite element method to create a database of specklegram images, covering the temperature range between 0 °C and 100 °C. With the prediction tests, we showed that both models can cover the entire proposed temperature range and achieve an accuracy of 99.5%, for the classification model, and a mean absolute error of 2.3 °C, in the regression model. We believe that these results show that the strategies implemented can improve the metrological capabilities of this type of sensor.

Numerical study using finite element method for the thermal response of fiber specklegram sensors with changes in the length of the sensing zone

The response of fiber specklegram sensors (FSSs) is given as function of variations in the intensity distribution of the modal interference pattern or speckle pattern induced by external disturbances. In the present work, the behavior of a FSS sensing scheme under thermal perturbations is studied by means of computational simulations of the speckle patterns. These simulations are generated by applying the finite element method (FEM) to the modal interference in optical fibers as a function of the thermal disturbance and the length of the sensing zone. A correlation analysis is performed on the images generated in the simulations to evaluate the dependence between the changes in the speckle pattern grains and the intensity of the applied disturbance. The numerical simulation shows how the building characteristic of the length of sensing zone, combined with image processing, can be manipulated to control the metrological performance of the sensors.

High-Sensitivity Refractive Index Sensor Based on a Cascaded Core-Offset and Macrobending Single-Mode Fiber Interferometer

A high-sensitivity Mach–Zehnder interferometer (MZI) based on the cascaded core-offset and macrobending fiber structure is proposed for refractive index (RI) measurement. The core-offset structure makes the fiber core mode couple to the cladding modes, and some of them recouple back to the fiber core at the macrobending structure forming a model interference effect. The liquid RI can be measured by monitoring the spectral shift of the modal interference. The RI sensing performances for the interferometers with different macrobending radii and core offsets are investigated experimentally. Experimental results show that when the core offset is 2 μm and the macrobending radius is 5.5 mm, the sensitivity can reach 699.95 nm/RIU for the RI of 1.43. The temperature dependence for the proposed sensor is also tested, and a temperature sensitivity of 0.112 nm/°C is obtained.

Giant refractometric sensitivity by combining extreme optical Vernier effect and modal interference

The optical Vernier effect consists of overlapping responses of a sensing and a reference interferometer with slightly shifted interferometric frequencies. The beating modulation thus generated presents high magnified sensitivity and resolution compared to the sensing interferometer, if the two interferometers are slightly out of tune with each other. However, the outcome of such a condition is a large beating modulation, immeasurable by conventional detection systems due to practical limitations of the usable spectral range. We propose a method to surpass this limitation by using a few-mode sensing interferometer instead of a single-mode one. The overlap response of the different modes produces a measurable envelope, whilst preserving an extremely high magnification factor, an order of magnification higher than current state-of-the-art performances. Furthermore, we demonstrate the application of that method in the development of a giant sensitivity fibre refractometer with a sensitivity of around 500 µm/RIU (refractive index unit) and with a magnification factor over 850.

Investigation of Precursors in VLF Subionospheric Signals Related to Strong Earthquakes (M > 7) in Western China and Possible Explanations

Earthquakes may disturb the lower ionosphere through various coupling mechanisms during their seismogenic and coseismic periods. The VLF signal radiated from ground-based transmitters is affected when it passes near the disturbed region above the seismogenic area, and this anomaly can be recorded by ground-based VLF receivers. In this paper, the seismic anomalies before two strong earthquakes (M > 7) that occurred in western China were detected using the ground-based observation of VLF signal; the possible reasons for the anomalies were discussed using full wave simulation. The amplitude of the VLF signals observed by the link between NOV, KHA transmitter, and VLF receivers at Ya’an and Tonghai show obvious anomaly by nighttime fluctuation analysis. The simulated results demonstrate that the anomalies could have been induced by ascending/descending of the bottom height of the ionosphere, caused by depletion/increase in D region electron density. The simulated result also illustrates that terminator time shift could have been induced by descending of the bottom boundary of the ionosphere, which is due to modal interference between different wave modes.