scholarly journals Analytical solution of CO2 mass flux measurement with Non-Dispersive Infrared sensors for soil in diffusive and advective-diffusive regime: Tool for the continuous and telemetric measurement of volcanic gases in an open chamber

2021 ◽  
Vol 48 (2) ◽  
Author(s):  
Nicolás Oliveras
Keyword(s):  
Embedded System ◽  
Mass Flux ◽  
Sensor Arrays ◽  
Flux Measurement ◽  
Infrared Sensors ◽  
Mathematical Solution ◽  
Diffusive Regime ◽  
Volcanic Monitoring ◽  
Single Sensor ◽  
Carbon Dioxide Co2

Measuring the carbon dioxide (CO2) mass flux in a volcanic environment is necessary for volcanic monitoring. CO2 mass flux must be measured continuously and telemetrically to get, almost in real-time, a better understanding of the dynamics of the volcanic degassing processes, contributing to the building, together with other monitoring technics, of a volcano behavior model. This study presents two analytical solutions, 1) a simple diffuse solution and 2) an advective-diffusive solution, which both implement NDIR (Non-Dispersive Infrared Emitter) sensor arrays in an open chamber (diffusion chimney) and an exchange chamber (gas interchanger). The first system, for which the gas speed is negligible, despite being basic (with values reflected in the slope of an equation line), introduces mass flux calculations with a single sensor NDIR. For the second system, where the gas speed is part of the equation, another mathematical solution and three measuring points are required, which demands the system to include a se­cond NDIR sensor for the correct mathematical solution of the equations system. In addition, an embedded system can automate the method by calibrating, controlling an agitation fan, and recording temperature, pressure, and mass flux in volcanic soils at the surface. Since this theoretically proposed method needs to be tested, experimental data are expected to validate the measurement of CO2 mass flux, which will be used as a helpful tool for volcanic monitoring.

scholarly journals Greenhouse gas flux measurements in a forestry-drained peatland indicate a large carbon sink

2011 ◽  
Vol 8 (11) ◽  
pp. 3203-3218 ◽  
Author(s):  
A. Lohila ◽  
K. Minkkinen ◽  
M. Aurela ◽  
J.-P. Tuovinen ◽  
T. Penttilä ◽  
...  
Keyword(s):  
Carbon Sink ◽  
Accumulation Rate ◽  
Peat Soil ◽  
Net Ecosystem Exchange ◽  
Flux Measurement ◽  
Co2 Exchange ◽  
Co2 Uptake ◽  
Flux Measurements ◽  
Ch4 And N2o ◽  
Carbon Dioxide Co2

Abstract. Drainage for forestry purposes increases the depth of the oxic peat layer and leads to increased growth of shrubs and trees. Concurrently, the production and uptake of the greenhouse gases carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) change: due to the accelerated decomposition of peat in the presence of oxygen, drained peatlands are generally considered to lose peat carbon (C). We measured CO2 exchange with the eddy covariance (EC) method above a drained nutrient-poor peatland forest in southern Finland for 16 months in 2004–2005. The site, classified as a dwarf-shrub pine bog, had been ditched about 35 years earlier. CH4 and N2O fluxes were measured at 2–5-week intervals with the chamber technique. Drainage had resulted in a relatively little change in the water table level, being on average 40 cm below the ground in 2005. The annual net ecosystem exchange was −870 ± 100 g CO2 m−2 yr−1 in the calendar year 2005, indicating net CO2 uptake from the atmosphere. The site was a small sink of CH4 (−0.12 g CH4 m−2 yr−1) and a small source of N2O (0.10 g N2O m−2 yr−1). Photosynthesis was detected throughout the year when the air temperature exceeded −3 °C. As the annual accumulation of C in the above and below ground tree biomass (175 ± 35 g C m−2) was significantly lower than the accumulation observed by the flux measurement (240 ± 30 g C m−2), about 65 g C m−2 yr−1 was likely to have accumulated as organic matter into the peat soil. This is a higher average accumulation rate than previously reported for natural northern peatlands, and the first time C accumulation has been shown by EC measurements to occur in a forestry-drained peatland. Our results suggest that forestry-drainage may significantly increase the CO2 uptake rate of nutrient-poor peatland ecosystems.

Study on Mass Flux Measurement Methods of Gas Based on Scanning Wavelength Modulation Spectroscopy

2016 ◽  
Vol 43 (9) ◽  
pp. 0904006
Author(s):  
屈东胜 Qu Dongsheng ◽  
洪延姬 Hong Yanji ◽  
王广宇 Wang Guangyu ◽  
王明东 Wang Mingdong ◽  
潘虎 Pan Hu
Keyword(s):  
Mass Flux ◽  
Flux Measurement ◽  
Wavelength Modulation Spectroscopy ◽  
Measurement Methods ◽  
Wavelength Modulation ◽  
Modulation Spectroscopy

scholarly journals A Modified Bayesian Framework for Multi-Sensor Target Tracking with Out-of-Sequence-Measurements

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3821
Author(s):  
Yifang Shi ◽  
Sundas Qayyum ◽  
Sufyan Ali Memon ◽  
Uzair Khan ◽  
Junaid Imtiaz ◽  
...  
Keyword(s):  
High Speed ◽  
Mean Squared Error ◽  
Surveillance Systems ◽  
Infrared Sensors ◽  
Multiple Sensors ◽  
Cluttered Environment ◽  
Detection And Tracking ◽  
Single Sensor ◽  
A New Technique ◽  
Proposed Modification

Target detection and tracking is important in military as well as in civilian applications. In order to detect and track high-speed incoming threats, modern surveillance systems are equipped with multiple sensors to overcome the limitations of single-sensor based tracking systems. This research proposes the use of information from RADAR and Infrared sensors (IR) for tracking and estimating target state dynamics. A new technique is developed for information fusion of the two sensors in a way that enhances performance of the data association algorithm. The measurement acquisition and processing time of these sensors is not the same; consequently the fusion center measurements arrive out of sequence. To ensure the practicality of system, proposed algorithm compensates the Out of Sequence Measurements (OOSMs) in cluttered environment. This is achieved by a novel algorithm which incorporates a retrodiction based approach to compensate the effects of OOSMs in a modified Bayesian technique. The proposed modification includes a new gating strategy to fuse and select measurements from two sensors which originate from the same target. The state estimation performance is evaluated in terms of Root Mean Squared Error (RMSE) for both position and velocity, whereas, track retention statistics are evaluated to gauge the performance of the proposed tracking algorithm. The results clearly show that the proposed technique improves track retention and and false track discrimination (FTD).

scholarly journals An Electronic Remote Snow-Drift Gauge

1981 ◽  
Vol 27 (95) ◽  
pp. 164-174 ◽  
Author(s):  
H. Gubler
Keyword(s):  
Pulse Rate ◽  
Mass Flux ◽  
Flux Measurement ◽  
Output Pulse ◽  
Physical Factors ◽  
Fracture Zones ◽  
Snow Drift ◽  
Photoelectric Sensor

AbstractSnow transportation by wind in potential avalanche fracture zones is a very important parameter for avalanche forecasts. A special battery-powered photoelectric sensor has been developed by the Eidg. Institut für Schnee- und Lawinenforschung, Weissfluhjoch/Davos. The output pulse rate is proportional to the mass flux (units of kg m–2s–1). Drift particles larger than 50 μm in diameter are classified according to their volumes in five classes. The accuracy of the flux measurement is ±50% and is limited by physical factors and not by the apparatus.

A Vehicle On-Board Alcohol Detection System Based on Integrated Multi-Sensors

2012 ◽  
Vol 490-495 ◽  
pp. 91-94 ◽  
Author(s):  
Li Fu ◽  
Jun Xiang Wang
Keyword(s):  
Embedded System ◽  
Information Fusion ◽  
Detection System ◽  
High Sensitivity ◽  
Visual Sensor ◽  
Dangerous Driving ◽  
Alcohol Sensor ◽  
Single Sensor ◽  
Sensor Information ◽  
Current Detection

A design and implementation of a detection system for dangerous driving was proposed based on multi-sensor-fusion. It is actually an embedded system consisting of visual,sensor, acceleration sensor, alcohol sensor input, and ARM cortex-M3 microcontroller. Experiment results show that the system has high linearity, high sensitivity,and excellent real-time performance. It can be further used to validate the multi-sensor information fusion algorithms in the field for improving the low reliability of the current detection by using one single-sensor method

scholarly journals Flipped parameter technique applied on source localization in energy constraint sensor arrays

2009 ◽  
Vol 7 (1) ◽  
pp. 7-22
Author(s):  
Vlastimir Pavlovic ◽  
Zoran Velickovic
Keyword(s):  
Time Delay ◽  
Source Localization ◽  
Cross Correlation ◽  
Sensor Arrays ◽  
Time Delay Estimation ◽  
Peak Time ◽  
Coherent Signals ◽  
Distributed Sensor ◽  
Passive Source Localization ◽  
Single Sensor

In this paper novel flipped parameter technique (FPT) for time delay estimation (TDE) in source localization problem is described. We propose passive source localization technique based on the development of an energy efficient algorithm that can reduce intersensor and interarray communication. We propose a flipped parameter (FP) which can be defined for any sensor in distributed sensor subarrays during the observation period. Unlike classical TDE methods that evaluate cross-correlation function, FPT requires evaluation based upon single sensor signal. The computed cross correlation between a signal and its analytic 'flipped' pair (flipped correlation) is a smooth function which peak (time delay) can be accurately detected. Flipped parameters are sufficient to determine all differential delays of the signals related to the same source. The flipped parameter technique can be used successfully in two-step methods of passive source localization with significantly less energy in comparison to the classic cross correlation. The use of FPT method is especially significant for the energy constrain distributed sensor subarrays. Using synthetic seismic signals, we illustrate the error of the source localization for classical and proposed method in the presence of noise. We demonstrate the performance improvement in noise environment of the proposed technique in comparison to the classic methods that use real signals. The proposed technique gives accurate results for both coherent and non-coherent signals.

OPTICAL MEMS TECHNOLOGIES FOR ELECTRICALLY TUNABLE MULTI-SPECTRAL SHORT-WAVE INFRARED SENSORS AND ARRAYS

2008 ◽  
Vol 18 (04) ◽  
pp. 1035-1044 ◽  
Author(s):  
JASON S. MILNE ◽  
JOHN M. DELL ◽  
ADRIAN J. KEATING ◽  
LORENZO FARAONE
Keyword(s):  
Short Wave ◽  
Sensor Technology ◽  
Future Research ◽  
Sensor Design ◽  
Infrared Sensors ◽  
Optical Mems ◽  
Ongoing Research ◽  
Mems Technology ◽  
Single Sensor ◽  
Future Research Directions

Optical MEMS technology combined with broadband infrared sensor technology is used to realize wavelength-tunable infrared sensors. This paper describes the ongoing research into one such sensor design based on an electrically tunable Fabry-Pérot cavity. Theory, measured results and future research directions are presented and discussed for the single-sensor design currently being developed, in the context of the intended application of this technology; the development of lightweight, portable and robust multi-spectral imaging systems.

scholarly journals Effects of particle shape on mass flux measurement of drifting snow by snow particle counter

2005 ◽  
Vol 67 (6) ◽  
pp. 493-503 ◽  
Author(s):  
Takeshi SATO ◽  
Shigeto MOCHIZUKI ◽  
Kenji KOSUGI ◽  
Masaki NEMOTO
Keyword(s):  
Mass Flux ◽  
Particle Shape ◽  
Flux Measurement ◽  
Particle Counter ◽  
Drifting Snow ◽  
Snow Particle

scholarly journals Microcontroller Implementation of Support Vector Machine for Detecting Blood Glucose Levels Using Breath Volatile Organic Compounds

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2283 ◽  
Author(s):  
Matthew Boubin ◽  
Sudhir Shrestha
Keyword(s):  
Support Vector Machine ◽  
Blood Glucose ◽  
Volatile Organic Compounds ◽  
Embedded System ◽  
Organic Compounds ◽  
Sensor Arrays ◽  
Support Vector ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Volatile Organic

This paper presents an embedded system-based solution for sensor arrays to estimate blood glucose levels from volatile organic compounds (VOCs) in a patient’s breath. Support vector machine (SVM) was trained on a general-purpose computer using an existing SVM library. A training model, optimized to achieve the most accurate results, was implemented in a microcontroller with an ATMega microprocessor. Training and testing was conducted using artificial breath that mimics known VOC footprints of high and low blood glucose levels. The embedded solution was able to correctly categorize the corresponding glucose levels of the artificial breath samples with 97.1% accuracy. The presented results make a significant contribution toward the development of a portable device for detecting blood glucose levels from a patient’s breath.

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