A polymer optical fiber strain sensor with extended dynamic range is reported. The proposed algorithm resets the reference fiber status depending on the magnitude of the specklegram deviation so the correlation coefficient never saturates, yielding a continuous response over the full range for both positive and negative strains. The technique was evaluated on the measurement of axial strains using a ZEONEX core, poly(methyl methacrylate) cladding multimode fiber, presenting reproducible results with 3 × 10 − 3 μϵ − 1 sensitivity (∼15 μϵ resolution) within a 22,600 μϵ interval. In contrast to the available approaches, the presented method can retrieve the strain direction and does not require intensive image processing, thus providing a simple and reliable technique for mechanical measurements using multimode optical fibers.
An optical fiber tactile sensor based on specklegram analysis is demonstrated. The system consists of microbending transducers attached to semi-rigid plates and distributed in form of array. The specklegrams produced by the multimode fibers are recorded and them the variations on fiber status, related to force magnitude, are assessed by specklegrams correlation. Finally, the spatial information was obtained by using a data fusion approach based on Bayesian inference. The sensor presented ∼0.08 N sensitivity and ∼1 mm resolution. Moreover, the data fusion technique provided the estimation of force distribution over a 30 × 30 mm2 area using only 3 fibers.
The identification of hand postures based on force myography (FMG) measurements using a fiber specklegram sensor is reported. The microbending transducers were attached to the user forearm in order to detect the radial forces due to hand movements, and the normalized intensity inner products of output specklegrams were computed with reference to calibration positions. The correlation between measured specklegrams and postures was carried out by artificial neural networks, resulting in an overall accuracy of 91.3% on the retrieval of hand configuration.
The measurement of concentration in colloidal silica nanoparticles and quartz nanocrystals dispersions by using an optical fiber reflectometer is reported. The reflected light intensities assessed by the fiber sensor were applied on the computation of autocorrelation functions, and the decay rates were associated to the colloids concentrations. The sensor provided reliable results, with sensitivities of 0.45 wt% ms and 0.23 wt% ms on the analysis of quartz and silica dispersions, respectively, for concentrations <1wt%. The differences on decay rate profiles are probably due to the differences on particles morphology and average dimension, as observed in the scanning electron microscopy images.
The application of a Fresnel-based fiber sensor on real-time monitoring of the fermentation process in bioethanol
production is reported. The fiber was placed inside the bioreactor, and experiments were conducted by using glucose
solution and sugarcane syrup as substrates for fermentation. When the sugar is completely consumed, there is no
production of ethanol, causing the sample concentration to become constant, as well as the reflected light intensity.
Therefore, the sensor can be used to predict the ideal moment to terminate the process. The results were confirmed by
additional laboratory analysis, making this an alternative technology for optimization of bioethanol production.
A flexible and low-cost optical fiber transducer based on light attenuation by microbending was designed for the
measurement of angular displacements. The transducer was tested for predetermined rotations, presenting a higher
sensitivity for angles >10° by spacing the periodicity of the deformers by 2 mm. In addition, the performance on the
measurement of angles <10° was also enhanced by the specklegram analysis, yielding to a linear response. Furthermore,
the glove-mounted sensor was applied on the detection of the proximal interphalangeal joint, by performing the
calibration by artificial neural networks, resulting in calculated angle values compatible to the nominal ones.
The measurement of process streams and effluents from sugar-ethanol industry by using optical fiber sensor based on
Fresnel reflection principle is reported. Firstly, binary sucrose-water and ethanol-water solutions were measured in order
to determine the calibration curves. Secondly, the co-products from various processing stages were analyzed in order to
identify the sucrose or ethanol concentration. The absolute error was calculated by comparison between the nominal
concentration values obtained by plant laboratory analysis and the sensor response, yielding errors ≤ 5 wt% and ≤ 5 vol%
for sucrose and ethanol content, respectively. The fiber sensor provided reliable results even for samples with more
complex compositions than pure sucrose or ethanol solutions, with perspectives of application on the several stages of
the plant facility.
The real-time determination of hydro-alcoholic concentration in alcohol distillation plants is a primordial condition in
order to preserve the quality and reduce production losses. Presented research proposes a Fresnel reflectometric optical
fiber sensor for the determination of hydro-alcoholic concentration in liquids. The intensity of reflected light and the
sample temperature are continuously measured and processed by a fast algorithm. Calibration curves were prepared for a
range from 0 to 100% of water in alcohol (ethanol) and adjusted to second order polynomials. According to functional
tests, sensor provides maximal error of 1.3 % for concentration values and proportionates practically real-time analysis.