scholarly journals Fabrication of Optical Fibers with Multiple Coatings for Swelling-Based Chemical Sensing

Micromachines ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 941
Author(s):  
Dorel Dorobantu ◽  
Alin Jderu ◽  
Marius Enachescu ◽  
Dominik Ziegler
Keyword(s):  
Optical Fibers ◽  
Chemical Sensing ◽  
Simultaneous Detection ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Medical Diagnostics ◽  
Single Fiber ◽  
Volume Changes ◽  
Fiber Optical ◽  
Agriculture Water

We discuss distributed chemical sensing based on the swelling of coatings of optical fibers. Volume changes in the coating induce strain in the fiber’s glass core, provoking a local change in the refractive index which is detectable by distributed fiber optical sensing techniques. We describe methods to realize different coatings on a single fiber. Simultaneous detection of swelling processes all along the fiber opens the possibility to interrogate thousands of differently functionalized sections on a single fiber. Principal component analysis is used to enable sensors for environmental monitoring, food analysis, agriculture, water quality monitoring, or medical diagnostics.

scholarly journals Swelling-Based Distributed Chemical Sensing with Standard Acrylate Coated Optical Fibers

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 718
Author(s):  
Sina Sedighi ◽  
Marcelo A. Soto ◽  
Alin Jderu ◽  
Dorel Dorobantu ◽  
Marius Enachescu ◽  
...  
Keyword(s):  
Optical Fiber ◽  
Optical Fibers ◽  
Chemical Sensing ◽  
Low Cost ◽  
Refractive Index Change ◽  
Water Quality Monitoring ◽  
Medical Diagnostics ◽  
Optical Frequency Domain Reflectometry ◽  
Frequency Domain Reflectometry ◽  
Agriculture Water

Distributed chemical sensing is demonstrated using standard acrylate coated optical fibers. Swelling of the polymer coating induces strain in the fiber’s silica core provoking a local refractive index change which is detectable all along an optical fiber by advanced distributed sensing techniques. Thermal effects can be discriminated from strain using uncoated fiber segments, leading to more accurate strain readings. The concept has been validated by measuring strain responses of various aqueous and organic solvents and different chain length alkanes and blends thereof. Although demonstrated on a short range of two meters using optical frequency-domain reflectometry, the technique can be applied to many kilometer-long fiber installations. Low-cost and insensitive to corrosion and electromagnetic radiation, along with the possibility to interrogate thousands of independent measurement points along a single optical fiber, this novel technique is likely to find applications in environmental monitoring, food analysis, agriculture, water quality monitoring, or medical diagnostics.

scholarly journals Swelling-Based Chemical Sensing With Unmodified Optical Fibers

2021 ◽  
Author(s):  
Alin Jderu ◽  
Dorel Dorobantu ◽  
Dominik Ziegler ◽  
Marius Enachescu
Keyword(s):  
Water Quality ◽  
Optical Fibers ◽  
Food Processing ◽  
Chemical Sensing ◽  
Low Cost ◽  
Water Quality Monitoring ◽  
Medical Diagnostics ◽  
Distributed Sensing ◽  
Quality Monitoring ◽  
Strain Sensing

AbstractWe use distributed fiber optic strain sensing to examine swelling of the fiber’s polymer coating. The distributed sensing technique that uses unmodified low-cost telecom fibers opens a new dimension of applications that include leak detection, monitoring of water quality, and waste systems. On a short-range length scale, the technology enables “lab-on-a-fiber” applications for food processing, medicine, and biosensing for instance. The chemical sensing is realized with unmodified low-cost telecom optical fibers, namely, by using swelling in the coating material of the fiber to detect specific chemicals. Although generic and able to work in various areas such as environmental monitoring, food analysis, agriculture or security, the proposed chemical sensors can be targeted for water quality monitoring, or medical diagnostics where they present the most groundbreaking nature. Moreover, the technique is without restrictions applicable to longer range installations.

scholarly journals Unravelling Plant-Pathogen Interactions: Proximal Optical Sensing as an Effective Tool for Early Detect Plant Diseases

2021 ◽  
Vol 5 (1) ◽  
pp. 18
Author(s):  
Mafalda Reis-Pereira ◽  
Rui C. Martins ◽  
Aníbal Filipe Silva ◽  
Fernando Tavares ◽  
Filipe Santos ◽  
...  
Keyword(s):  
Optical Fibers ◽  
Optical Sensing ◽  
Principal Component ◽  
Plant Diseases ◽  
Bacterial Suspension ◽  
Control Group ◽  
Post Inoculation ◽  
Early Disease Detection ◽  
Run Off ◽  
Vis Spectroscopy

This study analyzed the potential of proximal optical sensing as an effective approach for early disease detection. A compact, modular sensing system, combining direct UV–Vis spectroscopy with optical fibers, supported by a principal component analysis (PCA), was applied to evaluate the modifications promoted by the bacteria Xanthomonas euvesicatoria in tomato leaves (cv. cherry). Plant infection was achieved by spraying a bacterial suspension (108 CFU mL−1) until run-off occurred, and a similar approach was followed for the control group, where only water was applied. A total of 270 spectral measurements were performed on leaves, on five different time instances, including pre- and post-inoculation measurements. PCA was then applied to the acquired data from both healthy and inoculated leaves, which allowed their distinction and differentiation, three days after inoculation, when unhealthy plants were still asymptomatic.

Two Fiber Optical Fiber Thermometry

2000 ◽  
Author(s):  
Matthew R. Jones ◽  
Jeffery T. Farmer ◽  
Shawn P. Breeding
Keyword(s):  
Optical Fiber ◽  
Elevated Temperatures ◽  
Systematic Errors ◽  
Radiative Flux ◽  
Metallic Coating ◽  
Temperature Measurements ◽  
Single Fiber ◽  
Random Errors ◽  
Fiber Optical

Abstract An optical fiber thermometer consists of an optical fiber whose sensing tip is given a metallic coating. The sensing tip of the fiber forms an isothermal cavity, and the emission from this cavity is approximately equal to the emission from a blackbody. Temperature readings are obtained by measuring the spectral radiative flux at the end of the fiber at two wavelengths. The ratio of these measurements is used to infer the temperature at the sensing tip. However, readings from optical fiber thermometers are corrupted by emission from the fiber when extended portions of the probe are exposed to elevated temperatures. This paper describes several ways in which the reading from a second fiber can be used to correct the corrupted temperature measurements. It is shown that two of the correction methods result in significant reductions in the systematic errors. However, these methods are sensitive to random errors, so it is preferable to use a single fiber OFT if the uncertainties in the measurements are large.

scholarly journals Quantifying the Information Content of a Water Quality Monitoring Network Using Principal Component Analysis: A Case Study of the Freiberger Mulde River Basin, Germany

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 420 ◽  
Author(s):  
Thuy Hoang Nguyen ◽  
Björn Helm ◽  
Hiroshan Hettiarachchi ◽  
Serena Caucci ◽  
Peter Krebs
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
River Basin ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Component Analysis ◽  
Quality Monitoring ◽  
Critical Parameters ◽  
Spatial And Temporal Variation ◽  
Effectiveness Monitoring

Although river water quality monitoring (WQM) networks play an important role in water management, their effectiveness is rarely evaluated. This study aims to evaluate and optimize water quality variables and monitoring sites to explain the spatial and temporal variation of water quality in rivers, using principal component analysis (PCA). A complex water quality dataset from the Freiberger Mulde (FM) river basin in Saxony, Germany was analyzed that included 23 water quality (WQ) parameters monitored at 151 monitoring sites from 2006 to 2016. The subsequent results showed that the water quality of the FM river basin is mainly impacted by weathering processes, historical mining and industrial activities, agriculture, and municipal discharges. The monitoring of 14 critical parameters including boron, calcium, chloride, potassium, sulphate, total inorganic carbon, fluoride, arsenic, zinc, nickel, temperature, oxygen, total organic carbon, and manganese could explain 75.1% of water quality variability. Both sampling locations and time periods were observed, with the resulting mineral contents varying between locations and the organic and oxygen content differing depending on the time period that was monitored. The monitoring sites that were deemed particularly critical were located in the vicinity of the city of Freiberg; the results for the individual months of July and September were determined to be the most significant. In terms of cost-effectiveness, monitoring more parameters at fewer sites would be a more economical approach than the opposite practice. This study illustrates a simple yet reliable approach to support water managers in identifying the optimum monitoring strategies based on the existing monitoring data, when there is a need to reduce the monitoring costs.

scholarly journals Performance Analysis of Scattering-Level Multiplexing (SLMux) in Distributed Fiber-Optic Backscatter Reflectometry Physical Sensors

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2595 ◽  
Author(s):  
Daniele Tosi ◽  
Carlo Molardi ◽  
Wilfried Blanc ◽  
Tiago Paixão ◽  
Paulo Antunes ◽  
...  
Keyword(s):  
Optical Fibers ◽  
Rayleigh Scattering ◽  
Fiber Optic ◽  
Single Fiber ◽  
Distributed Sensor ◽  
The Core ◽  
Physical Sensors ◽  
Core Section ◽  
Boundary Limits ◽  
Multiple Fibers

Optical backscatter reflectometry (OBR) is a method for the interrogation of Rayleigh scattering occurring in each section of an optical fiber, resulting in a single-fiber-distributed sensor with sub-millimeter spatial resolution. The use of high-scattering fibers, doped with MgO-based nanoparticles in the core section, provides a scattering increase which can overcome 40 dB. Using a configuration-labeled Scattering-Level Multiplexing (SLMux), we can arrange a network of high-scattering fibers to perform a simultaneous scan of multiple fiber sections, therefore extending the OBR method from a single fiber to multiple fibers. In this work, we analyze the performance and boundary limits of SLMux, drawing the limits of detection of N-channel SLMux, and evaluating the performance of scattering-enhancement methods in optical fibers.

Exposed-core chalcogenide microstructured optical fibers for chemical sensing

2013 ◽  
Author(s):  
Johann Troles ◽  
Perrine Toupin ◽  
Laurent Brilland ◽  
Catherine Boussard-Plédel ◽  
Bruno Bureau ◽  
...  
Keyword(s):  
Optical Fibers ◽  
Chemical Sensing ◽  
Microstructured Optical Fibers

scholarly journals Application of multivariate statistical techniques in the water quality assessment of Danube river, Serbia

2015 ◽  
Vol 41 (4) ◽  
pp. 96-103 ◽  
Author(s):  
Danijela Voza ◽  
Milovan Vukovic ◽  
Ljiljana Takic ◽  
Djordje Nikolic ◽  
Ivana Mladenovic-Ranisavljevic
Keyword(s):  
Water Quality ◽  
Water Quality Management ◽  
Surface Water Quality ◽  
Principal Component ◽  
Water Quality Assessment ◽  
Water Quality Monitoring ◽  
Danube River ◽  
Multivariate Techniques ◽  
Data Set ◽  
Political Issue

AbstractThe aim of this article is to evaluate the quality of the Danube River in its course through Serbia as well as to demonstrate the possibilities for using three statistical methods: Principal Component Analysis (PCA), Factor Analysis (FA) and Cluster Analysis (CA) in the surface water quality management. Given that the Danube is an important trans-boundary river, thorough water quality monitoring by sampling at different distances during shorter and longer periods of time is not only ecological, but also a political issue. Monitoring was carried out at monthly intervals from January to December 2011, at 17 sampling sites. The obtained data set was treated by multivariate techniques in order, firstly, to identify the similarities and differences between sampling periods and locations, secondly, to recognize variables that affect the temporal and spatial water quality changes and thirdly, to present the anthropogenic impact on water quality parameters.

scholarly journals A Multivariate and Spatiotemporal Analysis of Water Quality in Code River, Indonesia

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Mochamad A. Pratama ◽  
Yan D. Immanuel ◽  
Dwinanti R. Marthanty
Keyword(s):  
Water Quality ◽  
Land Cover ◽  
Agricultural Land ◽  
Water Quality Management ◽  
Temporal Trends ◽  
Oxygen Demand ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Quality Data ◽  
Water Quality Data

The efficacy of a water quality management strategy highly depends on the analysis of water quality data, which must be intensively analyzed from both spatial and temporal perspectives. This study aims to analyze spatial and temporal trends in water quality in Code River in Indonesia and correlate these with land use and land cover changes over a particular period. Water quality data consisting of 15 parameters and Landsat image data taken from 2011 to 2017 were collected and analyzed. We found that the concentrations of total dissolved solid, nitrite, nitrate, and zinc had increasing trends from upstream to downstream over time, whereas concentrations of parameter biological oxygen demand, cuprum, and fecal coliform consistently undermined water quality standards. This study also found that the proportion of natural vegetation land cover had a positive correlation with the quality of Code River’s water, whereas agricultural land and built-up areas were the most sensitive to water pollution in the river. Moreover, the principal component analysis of water quality data suggested that organic matter, metals, and domestic wastewater were the most important factors for explaining the total variability of water quality in Code River. This study demonstrates the application of a GIS-based multivariate analysis to the interpretation of water quality monitoring data, which could aid watershed stakeholders in developing data-driven intervention strategies for improving the water quality in rivers and streams.

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