Aerosol Extinction Uncertainty Determination for a Laser-Based Detecting System

Quantitative measurement of optic and aerosolic property of troposphere may be carried out from lidar system more easily and with low marginal cost than other system (i.e. satellite observation). The aim of this work is to show how extinction coefficient and water vapor concentration in troposphere may be educed from lidar signals at several altitudes and how uncertainty is close to acceptable value. Real data observations will be presented to demostrate uncertainty range on aerosolic extinction coefficient function

Noise Impact in Designed Conditioning System for Energy Harvesting Units in Biomedical Applications

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Editorial: Special Issue on Environmental Measurement and Instrumentation

This Special Issue contains expanded and enhanced versions of selected papers presented at the 2013 IMEKO TC19 Symposium on Environmental Monitoring

Sparsity of the Field Signal-Based Method for Improving Spatial Resolution in Antenna Sensor Array Processing

The goal of array processing is to gather information from propagating radio-wave signals, as their Direction Of Arrival (DOA). The estimation of the DOA can be carried out by extracting the information of interest from the steering vector relevant to the adopted antenna sensor array. Such task can be accomplished in a number of different ways. However, in source estimation problems, it is essential to make use of a processing algorithm which feature not only good accuracy under ideal working conditions, but also robustness against non-idealities such as noise, limitations in the amount of collectible data, correlation between the sources, and modeling errors. In this work particular attention is devoted to spectrum estimation approaches based on sparsity. Conventional algorithms based on Beamforming fail wherein the radio sources are not within Rayleigh resolution range which is a function of the number of sensors and the dimension of the array. DOA estimation techniques such as MUSIC (MUltiple Signal Classifications) allow having a larger spatial resolution compared to Beamforming-based procedures, but if the sources are very close and the Signal to Noise Ratio (SNR) level is low, the resolution turns to be low as well. A better resolution can be obtained by exploiting sparsity: if the number of sources is small, the power spectrum of the signal with respect to the location is sparse. In this way, sparsity can enhance the accuracy of the estimation. In this paper, an estimation procedure based on the sparsity of the radio signals and useful to improve the conventional MUSIC method is presented and analyzed. The sparsity level is set in order to focus the signal energy only along the actual direction of arrival. The obtained numerical results have shown an improvement of the spatial resolution as well as a reduced error in DOA estimation with respect to conventional techniques

Measurement: Food

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Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate

A SOLAR-POWERED WHITE LED-BASED UV-VIS SPECTROPHOTOMETRIC SYSTEM MANAGED BY PC FOR AIR POLLUTION DETECTION IN FARAWAY AND UNFRIENDLY LOCATIONS

This research work regards the design and realization of an absorption spectrophotometer based on a LED light source in place of the usually employed Xenon lamp. The advantage of the use of LED technology resides in several factors such as the reducing of the analyte temperature variations and thus noise generation, which occur if a Xenon light source is used, beside of the high luminous efficiency, reliability, operating duration, lower maintenance and a lower power consumption. This last factor allows to supply the entire designed apparatus using a solar panel thus making the system easly portable for use even in places where the electricity network is absent. An optical filtering system was realized in order to detect the analyte absorption for each wavelength range selected by the optical filters. A PC-interfaced PIC-based control unit used to manage the different functionalities required by the spectophotometer was realized and tested. The control unit acquires and processes, via the developed firmware, the raw data provided by different sensors employed in the system. The sensors are used to monitor analyte temperature and humidity values, to control the analyte pressure and to acquire the luminous intensity value of the light beam before and after passing through the analyte. Finally, the realized electronic control unit actuates different mechanical sections (stepper motor, solenoid valve), sincronyzing and controlling the data exchange between hardware sections, microcontroller and the PC

Accurate spectral estimation technique based on decimated linear predictor for leak detection in waterworks

Rural pipelines dedicated to water distribution, that is, waterworks, are essential for agriculture, notably plantations and greenhouse cultivation. Water is a primary resource for agriculture, and its optimized management is a key aspect. Saving water dispersion is not only an economic problem but also an environmental one. Spectral estimation of leakage is based on processing signals captured from sensors and/or transducers generally mounted on pipelines. There are different techniques capable of processing signals and displaying the actual position of leaks. Not all algorithms are suitable for all signals. That means, for pipelines located underground, for example, external vibrations affect the spectral response quality; then, depending on external vibrations/noises and flow velocity within pipeline, one should choose a suitable algorithm that fits better with the expected results in terms of leak position on the pipeline and expected time for localizing the leak. This paper presents findings related to the application of a decimated linear prediction (DLP) algorithm for agriculture and rural environments. In a certain manner, the application also detects the hydrodynamics of the water transportation. A general statement on the issue, DLP illustration, a real application and results are also include

MODELING AND DESIGNING A FULL BEAMFORMER FOR ACOUSTIC SENSING AND MEASUREMENT

Acoustic sensing is a viable approach for solving issues related to many applications, namely, biomedical, distance measurements, mechanical, health infrastructure monitoring, etc. It is generally sustainable and of no negative impact on the object under test. The use of acoustic sensing under beamforming technique is an important asset to be exploited, especially for the aforementioned applications. This paper illustrates a generalized approach of modeling and designing a full beamfomer using two specific classes: LCMP (Linear Constrained Minimum Power) beamformers that are used to overcome robustness limitations and MVDR (Minimum Variance Distortionless Response) beamformers. Any aspect of modeling and designing is always related to the DOA (Direction of Arrival). The obtained results are based on assumptions extracted from an actual case of constructed system