An Optimized Self-Compensated Solution for Temperature and Strain Cross-Sensitivity in FBG Interrogators Based on Edge Filter

Optical fiber sensors based on fiber Bragg gratings (FBGs) are prone to measurement errors if the cross-sensitivity between temperature and strain is not properly considered. This paper describes a self-compensated technique for canceling the undesired influence of temperature in strain measurement. An edge-filter-based interrogator is proposed and the central peaks of two FBGs (sensor and reference) are matched with the positive and negative slopes of a Fabry–Perot interferometer that acts as an optical filter. A tuning process performed by the grey wolf optimizer (GWO) algorithm is required to determine the optimal spectral characteristics of each FBG. The interrogation range is not compromised by the proposed technique, being determined by the spectral characteristics of the optical filter in accordance with the traditional edge-filtering interrogation. Simulations show that, by employing FBGs with optimal characteristics, temperature variations of 30 °C led to an average relative error of 3.4% for strain measurements up to 700μϵ. The proposed technique was experimentally tested under non-ideal conditions: two FBGs with spectral characteristics different from the optimized results were used. The temperature sensibility decreased by 50.8% as compared to a temperature uncompensated interrogation system based on an edge filter. The non-ideal experimental conditions were simulated and the maximum error between theoretical and experimental data was 5.79%, proving that the results from simulation and experimentation are compatible.

Enhancement of Solar Cell Modeling with MPPT Command Practice with an Electronic Edge Filter

A new photovoltaic cell modeling based on an electronically tunable edge filter is presented in this paper. The new model is subjected to temperature, illumination, and resistance variations. In addition, an MPPT (Maximum Power Point Tracker) command was exposed with a calculation algorithm based on a microcontroller card that used the behavior of an electronically tunable edge filter. The results confirm those published in the literature, showing the influence of the position of the leakage variation in our model, which can give more power. The simulation results show that the proposed command is efficient to determine the MPP point.

Adaptive Threshold Model in Google Earth Engine: A Case Study of Ulva prolifera Extraction in the South Yellow Sea, China

An outbreak of Ulva prolifera poses a massive threat to coastal ecology in the Southern Yellow Sea, China (SYS). It is a necessity to extract its area and monitor its development accurately. At present, Ulva prolifera monitoring by remote sensing imagery is mostly based on a fixed threshold or artificial visual interpretation for threshold selection, which has large errors. In this paper, an adaptive threshold model based on Google Earth Engine (GEE) is proposed and applied to extract U. prolifera in the SYS. The model first applies the Floating Algae Index (FAI) or Normalized Difference Vegetation Index (NDVI) algorithm on the preprocessed remote sensing images and then uses the Canny Edge Filter and Otsu threshold segmentation algorithm to extract the threshold automatically. The model is applied to Landsat8/OLI and Sentinel-2/MSI images, and the confusion matrix and cross-sensor comparison are used to evaluate the accuracy and applicability of the model. The verification results show that the model extraction of U. prolifera based on the FAI algorithm has higher accuracy (R2 = 0.99, RMSE = 5.64) and better robustness. However, when the average cloud cover is more than 70% in the image (based on the statistical results of multi-year cloud cover information), the model based on the NDVI algorithm has better applicability and can extract the algae distributed at the edge of the cloud. When the model uses the FAI algorithm, it is named FAI-COM (model based on FAI, the Canny Edge Filter, and Otsu thresholding). And when the model uses the NDVI algorithm, it is named NDVI-COM (model based on NDVI, the Canny Edge Filter, and Otsu thresholding). Therefore, the final extraction results are generated by supplementing NDVI-COM results on the basis of FAI-COM extraction results in this paper. The F1-score of U. prolifera extracted results is above 0.85. The spatiotemporal distribution of U. prolifera in the South Yellow Sea from 2016 to 2020 is obtained through the model calculation. Overall, the coverage area of U. prolifera shows a decreasing trend over the five years. It is found that the delay in recovery time of Porphyra yezoensis culture facilities in the Northern Jiangsu Shoal and the manual salvage and cleaning-up of U. prolifera in May are among the reasons for the smaller interannual scale of algae in 2017 and 2018.

Validation of biosignatures confirms the informative nature of fossil organic Raman spectra

Raman spectroscopy has facilitated rapid progress in the understanding of patterns and processes associated with biomolecule fossilization and revealed the preservation of biological and geological signatures in fossil organic matter. Nonetheless six large-scale statistical studies of Raman spectra of carbonaceous fossils, selected from a number of independent assessments producing similar trends, have been disputed. Alleon et al. (21) applied a wavelet transform analysis in an unconventional way to identify frequency components contributing to two baselined spectra selected from these studies and claimed similarities with a downloaded edge filter transmission spectrum. On the basis of indirect comparisons and qualitative observations they argued that all spectral features detected, including significant mineral peaks, can be equated to edge filter ripples and are therefore artefactual. Alleon et al. (21) extrapolated this conclusion to dispute not only the validity of n>200 spectra in the studies in question, but also the utility of Raman spectroscopy, a well established method, for analysing organic materials in general. Here we test the claims by Alleon et al. (21) using direct spectral comparisons and statistical analyses. We present multiple independent lines of evidence that demonstrate the original, biologically and geologically informative nature of the Raman spectra in question. We demonstrate that the methodological approach introduced by Alleon et al. (21) is unsuitable for assessing the quality of spectra and identifying noise within them. Statistical analyses of large Raman spectral data sets provide a powerful tool in the search for compositional patterns in biomaterials and yield invaluable insights into the history of life.

Low-cost interrogation system for dynamic sensor applications using a resin based fiber Fabry Perot filter

In this paper it will be presented a prototype of a low-cost power interrogator for dynamic sensor applications. The proposed system is based on the edge filter technique, where the slope of an in-house resin based Fabry Perot (FP) filter is used to actively filter the power of a narrowband laser centred at the middle part of the FP slope region. The interrogator is composed of a laser source, circulator, photodetector, Arduino board and laptop. Tests have been performed in order to check the viability of the system. Finally, the measurement of a pulse wave signal has been performed by embedding the FP sensor in a 3D printed elastic membrane and reading the signal through the proposed interrogator.

Prototypical Simulation of an Optical Edge Filter Design for Three Different Rayleigh Wavelengths Using Octave Software

Optical filters used specifically for special functions to block a particular wavelength or range of wavelength and transmit the rest of the spectrum have received research attention for the past few eras. Recently, optical filter based on multilayer coating are more focused due to potential to manipulate filter properties by changing layer thickness in order to apply in various fields. This Quarter wave stack (QWS) model design is one of the approaches to design optical filter such as edge filter. However, to obtain desire minimum specification need an optimization. Therefore, in this study aims to design optical edge filter based QWS model by optical matrix method in Octave software. In this design, MoS2 and Si are being choose for high (H) and low (L) refractive index materials respectively. The optimum twenty-four (24) number of layers are determined by calculating maximum transmittance obtained. The Rayleigh wavelength ( λex ) of 405 nm ,532 nm and 633 nm are selected and ‘glass|12HL|air’ configuration is set for the design simulation. Then, the cut-on wavelength (λcut-on) and cut-off wavelength ((λcut-off) of successful designed optical edge filter are measured. The result shows that the cut-on wavelength of 408.11 nm, 536 nm and 640.25 nm with minimum effective transmission (MET) of 32.3%, 31.3% and 32% respectively are obtained. In conclusion, this present study shows the deviation between the calculated value and simulation of about 0.2 nm,1.7 nm and 1.15 nm for each λex of 405 nm, 532 nm and 633 nm is determined. But for λcut-off, the value obtained are much higher than the calculated value. The MET of each filter is 32.3% ,31.3% and 32% for Rayleigh wavelength respectively.