Sensing with fiber specklegrams

A Machine Learning Specklegram Wavemeter (MaSWave) Based on a Short Section of Multimode Fiber as the Dispersive Element

Wavemeters are very important for precise and accurate measurements of both pulses and continuous-wave optical sources. Conventional wavemeters employ gratings, prisms, and other wavelength-sensitive devices in their design. Here, we report a simple and low-cost wavemeter based on a section of multimode fiber (MMF). The concept is to correlate the multimodal interference pattern (i.e., speckle patterns or specklegrams) at the end face of an MMF with the wavelength of the input light source. Through a series of experiments, specklegrams from the end face of an MMF as captured by a CCD camera (acting as a low-cost interrogation unit) were analyzed using a convolutional neural network (CNN) model. The developed machine learning specklegram wavemeter (MaSWave) can accurately map specklegrams of wavelengths up to 1 pm resolution when employing a 0.1 m long MMF. Moreover, the CNN was trained with several categories of image datasets (from 10 nm to 1 pm wavelength shifts). In addition, analysis for different step-index and graded-index MMF types was carried out. The work shows how further robustness to the effects of environmental changes (mainly vibrations and temperature changes) can be achieved at the expense of decreased wavelength shift resolution, by employing a shorter length MMF section (e.g., 0.02 m long MMF). In summary, this work demonstrates how a machine learning model can be used for the analysis of specklegrams in the design of a wavemeter.

Machine learning for sensing with a multimode exposed core fiber specklegram sensor

Fiber specklegram sensors (FSSs) traditionally use statistical methods to analyze specklegrams obtained from fibers for sensing purposes, but can suffer from limitations such as vulnerability to noise and lack of dynamic range. In this paper we demonstrate that deep learning improves the analysis of specklegrams for sensing, which we show here for both air temperature and water immersion length measurements. Two deep neural networks (DNNs); a convolutional neural network and a multi-layer perceptron network, are used and compared to a traditional correlation technique on data obtained from a multimode fiber exposed-core fiber. The ability for the DNNs to be trained against a random noise source such as specklegram translations is also demonstrated.

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.

Optical fiber specklegram sensor analysis by speckle pattern division

An optical fiber specklegram sensor interrogation method based on speckle pattern fragmentation is presented. The acquired specklegram images are divided in a square grid, creating sub-images that are further processed by a correlation technique, allowing the quantification of localized changes in the specklegrams. The methodology was tested on the assessment of linear displacements using a microbending transducer, by evaluating different grid sizes. For a 5×5 grid, a 2.53  mm^-1 sensitivity over a 0.27 mm range was obtained, representing an extension of 237.5% in comparison to the standard interrogation technique. Therefore, the presented technique allows enhancing the sensor dynamic range without modifying the experimental setup.

Numerical modeling of fiber specklegram sensors by using finite element method (FEM)

Although experimental advances in the implementation and characterization of fiber speckle sensor have been reported, a suitable model to interpret the speckle-pattern variation under perturbation is desirable but very challenging to be developed due to the various factors influencing the speckle pattern. In this work, a new methodology based on the finite element method (FEM) for modeling and optimizing fiber specklegram sensors (FSSs) is proposed. The numerical method allows computational visualization and quantification, in near field, of changes of a step multi-mode fiber (SMMF) specklegram, due to the application of a uniformly distributed force line (UDFL). In turn, the local modifications of the fiber speckle produce changes in the optical power captured by a step single-mode fiber (SSMF) located just at the output end of the SMMF, causing a filtering effect that explains the operation of the FSSs. For each external force, the stress distribution and the propagations modes supported by the SMMF are calculated numerically by means of FEM. Then, those modes are vectorially superposed to reconstruct each perturbed fiber specklegram. Finally, the performance of the sensing mechanism is evaluated for different radius of the filtering SSMF and force-gauges, what evidences design criteria for these kinds of measuring systems. Results are in agreement with those theoretical and experimental ones previously reported.

All-fiber spectrometer based on speckle pattern reconstruction

A standard multimode optical fiber can be used as a general purpose spectrometer after calibrating the wavelength dependent speckle patterns produced by interference between the guided modes of the fiber. A transmission matrix was used to store the calibration data and a robust algorithm was developed to reconstruct an arbitrary input spectrum in the presence of experimental noise. We demonstrate that a 20 meter long fiber can resolve two laser lines separated by only 8 pm. At the other extreme, we show that a 2 centimeter long fiber can measure a broadband continuous spectrum generated from a supercontinuum source. We investigate the effect of the fiber geometry on the spectral resolution and bandwidth, and also discuss the additional limitation on the bandwidth imposed by speckle contrast reduction when measuring dense spectra. Finally, we demonstrate a method to reduce the spectrum reconstruction error and increase the bandwidth by separately imaging the speckle patterns of orthogonal polarizations. The multimode fiber spectrometer is compact, lightweight, low cost, and provides high resolution with low loss.

Review of Random Phase Encoding in Volume Holographic Storage

Random phase encoding is a unique technique for volume hologram which can be applied to various applications such as holographic multiplexing storage, image encryption, and optical sensing. In this review article, we first review and discuss diffraction selectivity of random phase encoding in volume holograms, which is the most important parameter related to multiplexing capacity of volume holographic storage. We then review an image encryption system based on random phase encoding. The alignment of phase key for decryption of the encoded image stored in holographic memory is analyzed and discussed. In the latter part of the review, an all-optical sensing system implemented by random phase encoding and holographic interconnection is presented.

Specklegram in a multiple-mode fiber and its dependence on longitudinal modes of the laser source

A specklegram in a multimode fiber (MMF) has successfully been used as a sensor for detecting external disturbance. Our experiments showed that the sensitivity in the sensor with a multiple longitudinal-mode laser as its source was much higher than that with a single longitudinal-mode laser. In addition, the near-field pattern observations indicated that the coupling between different transverse modes in the MMF is quite weak. Based on the experimental results, a theoretical model for the speckle formation is proposed, taking a bend-caused phase factor into consideration. It is shown in the theoretical analysis that the interferences between different longitudinal modes make a larger contribution to the specklegram signals.

Impact and vibration detection in composite materials by using intermodal interference in multimode optical fibers

An optical fiber sensor based on the intermodal interference principle is integrated in a composite material to detect impacts and vibrations. Six fibers are integrated at the top of a carbon/epoxy composite panel so as to form a grid into the structure. Spectral and temporal responses to impacts and acoustic vibrations of the sensor are compared with a piezoelectric accelerometer. The tests proved the facility of integration and the high sensitivity of the device. The location of impacts is performed with this arrangement by measuring the arrival times of the front waves to the fibers.

Temperature-compensated fiber specklegram strain sensing with an adaptive joint transform correlator

A temperature-compensated fiber specklegram strain sensor with an adaptive joint transform correlator (JTC) is presented. By exploiting the dual-channel correlation of the fiber specklegram JTC, we can measure the temperature-compensated strain. Experimental results have shown that the strain sensitivity can be as high as 0.1 µstrain/1°C.

Analysis of a fiber specklegram sensor by using coupled-mode theory

The performance of the fiber specklegram sensor (FSS) by use of the waveguide coupled-mode theory is analyzed. The analyses are based on the microbending effect on the sensing fiber, in which we have found that the sensitivity of the FSS is affected by the core diameter and the bending geometry. Experimental confirmations of the analyses are also provided in which we have shown that experimental data are consistent with the analyses.

Dynamic fiber specklegram sensing

We introduce a concept of dynamic sensing that uses fiber speckle fields. By autonomously updating the fiber speckle patterns (i.e., using a moving reference to perform frame-to-frame comparison) on an electronically addressable spatial light modulator, we can exploit the dynamic fiber status. In other words, by joint transforming the rapidly changing speckle patterns from a sensing fiber, we can determine the dynamic aspects of the fiber status. For demonstration, dynamic displacement sensing is illustrated in which we have observed that the rate change and the trend of the fiber perturbation can indeed be detected. We note that the dynamic sensing technique can be applied to a variety of sensing parameters, e.g., strain, stress, temperature, and possibly seismic monitoring.

Application of a fiber-speckle hologram to fiber sensing

A sensitive fiber-speckle field sensor using a Ce:Fe-doped LiNbO(3) photorefractive fiber hologram is introduced. We have shown that the sensitivity of this photorefractive fiber specklegram sensor can be of the order of 0.05 µm. The proposed system would offer the widespread use of practical fiber-sensing applications.

Multimode fiber sensing by using mean-absolute speckle-intensity variation

We present a fiber-sensing technique that detects the mean-absolute speckle-intensity variation between the updated and the reference speckle pattern for determining the environmental perturbation factor (e.g., displacement, temperature, pressure, acoustic wave). We show that the proposed technique is highly sensitive and simple. One of the major advantages of the proposed technique is that it can perform a fast-response measurement with off-the-shelf electronic hardware. Experimental data for submicrometer displacement as well as temperature measurement are provided. To extend the dynamic range of the proposed technique, one can use an updated reference speckle pattern.

Submicrometer displacement sensing using inner-product multimode fiber speckle fields

A multimode fiber sensor using the intensity inner product of speckle fields is presented. The sensitivity and the dynamic range of the displacement sensing are quantitatively analyzed. We show that the sensitivity of displacement can be in the submicrometer range. Experimental performances show that the results are consistent with the calculated results.

Multichannel sensing with fiber specklegrams

A fiber specklegram sensor for multichannel sensing is presented. Analyses and experiments show that a fiber specklegram sensor (FSS) is highly sensitive to the modal phasing variation of a multimode-sensing fiber. It is shown that the FSS is less vulnerable to environmental factors than the two-arm interferometric fiber-sensing technique. Because the FSS processes a narrow spectral bandwidth, it is particularly suitable for wavelength multiplexing. One of the major advantages of the FSS must be the multiplexing capability, in which multiparameter sensing can be realized in a single fiber. Applications of the FSS system to acoustic-sensing array, structural fatigue monitoring, and smart emission detection are also discussed.