Optical fiber specklegram sensor analysis by speckle pattern division

Deep Learning-Based Simultaneous Temperature- and Curvature-Sensitive Scatterplot Recognition

Since light propagation in a multimode fiber (MMF) exhibits visually random and complex scattering patterns due to external interference, this study numerically models temperature and curvature through the finite element method in order to understand the complex interactions between the inputs and outputs of an optical fiber under conditions of temperature and curvature interference. The systematic analysis of the fiber's refractive index and bending loss characteristics determined its critical bending radius to be 15 mm. The temperature speckle atlas is plotted to reflect varying bending radii. An optimal end-to-end residual neural network model capable of automatically extracting highly similar scattering features is proposed and validated for the purpose of identifying temperature and curvature scattering maps of MMFs. The viability of the proposed scheme is tested through numerical simulations and experiments, the results of which demonstrate the effectiveness and robustness of the optimized network model.

Broadband intermodal fiber interferometer for sensor application: fundamentals and simulator

An intermodal fiber interferometer using the light from an incoherent broadband source has been considered analytically and implemented as a laboratory device. It was shown that this optical scheme could be used to measure external perturbations that cause a change in the optical length of a multimode fiber. The use of an optical spectrum analyzer and correlation functions approach in extracting the utility signal made it possible to achieve a linear response to the measured external perturbation and effective fading mitigation. A pair of integral coefficients was introduced: the contrast coefficient for characterization of the coherency of the operation regime, and the fading coefficient for estimating the signal stability against non-signal parasitic influences. Analytical expressions for the utility signal parameters were derived in dependence on the parameters of the light source, multimode fiber, and optical spectrum analyzer. The relationships among fiber length, width of the light source spectrum, and frequency resolution of the optical spectrum analyzer were stated for the optimum regime of interferometer operation. The simulation of the external perturbations performed at the elaborated device proved the applicability of the proposed scheme as a sensor of various physical quantities.

Speckle-based high-resolution multimodal soft sensing

Skin-like soft sensors are key components for human–machine interfaces; however, the simultaneous sensing of several types of stimuli remains challenging because large-scale sensor integration is required with numerous wire connections. We propose an optical high-resolution multimodal sensing approach, which does not require integrating multiple sensors. This approach is based on the combination of an optical scattering phenomenon, which can encode the information of various stimuli as a speckle pattern, and a decoding technique using deep learning. We demonstrate the simultaneous sensing of three different physical quantities—contact force, contact location, and temperature—with a single soft material. Another unique capability of the proposed approach is spatially continuous sensing with an ultrahigh resolution of few tens of micrometers, in contrast to previous multimodal sensing approaches. Furthermore, a haptic soft device is presented for a human–machine interface. Our approach encourages the development of high-performance smart skin-like sensors.

Sensing Using Light: A Key Area of Sensors

This invited featured paper offers a Doctrinal Conception of sensing using Light (SuL) as an "umbrella" in which any sensing approach using Light Sciences and Technologies can be easily included. The key requirements of a sensing system will be quickly introduced by using a bottom-up methodology. Thanks to this, it will be possible to get a general conception of a sensor using Light techniques and know some related issues, such as its main constituted parts and types. The case in which smartness is conferred to the device is also considered. A quick "flight" over 10 significant cases using different principles, techniques, and technologies to detect diverse measurands in various sector applications is offered to illustrate this general concept. After reading this paper, any sensing approach using Light Sciences and Technologies may be easily included under the umbrella: sensing using Light or photonic sensors (PS).

Correlation-Based Out-of-Plane Displacement Measurement for Optical Fiber Material

Due to the monitoring requirement of optical fiber industrial production, an out-of-plane displacement measurement method is proposed. Firstly, the in-plane displacements between two consecutive images, captured through a microscope with a CCD camera, are estimated by the Digital Speckle Correlation Method (DSCM). Subsequently, the out-of-plane displacement of optical fiber material can be obtained by the wedge model. Finally, the effectiveness of the method is verified experimentally by comparing the measurement data of routine practice with its theoretical values. Simulation and experimental results indicate that the absolute errors and the relative errors of the measurement by the optical microscope with a magnification of 50× are less than ±0.2 μm and 5%, respectively. The new method only needs two images obtained by the microscopic imaging system with a single camera to accomplish the measurement, which can significantly reduce the measurement time and complexity of the arrangement. Further, the method needs neither frequency domain conversion nor phase unwrapping operation, therefore, it is especially suitable for dynamic out-of-plane displacement measurement. The proposed method has been applied to the industrial uniformity and micro–nano-scale deformation monitoring of optical fiber image transmission materials.

Evaluation of image matching techniques for optical fiber specklegram sensor analysis

A quantitative study of image matching techniques applied to fiber specklegram sensor analysis is presented. The fiber status is modulated by a microbending transducer, so the output speckle field can be correlated to the input displacements. Once acquired and preprocessed, the specklegrams' variations were evaluated according to seven approaches. Although the average intensity did not provide reliable information per se, the correlation and sum of differences methods yielded ∼11  mm^-1 and ∼14  mm^-1 sensitivities, respectively, within a ∼0.06  mm range and low linearity and hysteresis errors, with enhancement possibility by intensity level cancellation. Moreover, the phase-only correlation and the mutual information metrics provided very high sensitivities (22  mm^-1 and 120  mm^-1, respectively) for a <0.02  mm range, making these techniques suitable for detecting subtle variations in the fiber status due to physical or chemical stimuli.

Fiber-Optic Point-Based Sensor Using Specklegram Measurement

Here, we report a fiber-optic point-based sensor to measure temperature and weight based on correlated specklegrams induced by spatial multimode interference. The device is realized simply by splicing a multimode fiber (MMF) to a single-mode fiber (SMF) with a core offset. A series of experiments demonstrates the approximately linear relation between the correlation coefficient and variation. Furthermore, we show the potential applications of the refractive index sensing of our device by disconnecting the splicing point of MMF and SMF. A modification of the algorithm in order to improve the sensitivity of the sensor is also discussed at the end of the paper.