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  • Open access
  • 87 Reads
The Cup Anemometer, a Fundamental Meteorological Instrument for the Wind Energy Industry
The cup anemometer has been used widely by the wind energy industry since its early beginning, covering two fundamental aspects: wind mill performance control and wind energy production forecast. Furthermore, despite modern technological advances such as LIDAR and SODAR, this cup anemometer remains clearly the most used instrument by the wind energy industry. Together with the major advantages of this instrument (precision, robustness), some issues must be taken into account by scientists and researchers when using it. Overspeeding, interaction with stream wakes due to allocation on masts and wind-mills, loss of performance due to wear and tear, change of performance due to different climatic conditions, checking of the maintenance status and recalibration, etc. On the other hand, although it seems that the cup anemometer has reached an optimal standardized configuration of three conical cups, some improvement could be done analyzing the rotor aerodynamics. In the present work a review of the research campaigns carried out at the IDR/UPM Institute to analyze cup anemometer performance is included. Several aspects of this instrument are examined: the calibration process and its possible effect on wind-mill Annual Energy Production (AEP), the loss of performances due to aging and wear and tear, the effect of changes of air density, the rotor aerodynamics, and the harmonic terms contained in the anemometer output signal and their possible relation to the anemometer performances.
  • Open access
  • 120 Reads
The Application of a Piezo-Resistive Cardiorespiratory Sensor System in an Automobile
Respiratory and heart failure are conditions that can occur with little warning and may also be difficult to predict. Therefore continuous monitoring of these bio-signals is advantageous for ensuring human health. The safety belt is mainly designed to secure the occupant of the vehicle in the event of an accident. In the current research a prototype of safety belt is developed, which is used to achieve the respiratory and heart signal, under laboratory conditions. The current safety belt is constructed using the copper ink based peizo-resistive material, which works on the principle of pressure exerted on the sensor due to the expansion of the thorax/abdomen area of the body for respiration and due to the principle of ballistocardiography for heart signal sensing. The research explains the process of manufacturing the safety belt, preparation of cardio-respiratory sensor and integration of these sensors into the safety belt.
  • Open access
  • 50 Reads
Analysis of Wireless Sensor Network Topology and Estimation of Optimal Network Deployment by Deterministic Radio Channel Characterization
The design and development of a Wireless Sensor Network (WSN) on an indoor scenario, where multipath propagation has special relevance, is often a difficult task that requires a long and tedious fieldwork that is not reusable later. This paper focuses on the validation of 3D Ray Launching simulation as an efficient method for reducing the time and effort required to design and develop a WSN on a complex indoor scenario, which can later be employed for different applications. Using a well tested deterministic method which offers reliable results, the most suitable antenna distribution and consequently a homogeneous power distribution could be achieved easily for different places and topologies. In this work the radioplanning procedure is validated in a prototype of a WSN Mobile Ad-Hoc Network (MANET), implementing a chain configuration deployed in a real indoor scenario, which is the entire floor of a university department, providing assessment on radio level, signal quality and power consumption. The use of deterministic tools in WSN deployment phases can aid in providing optimal layouts in terms of coverage, capacity and energy efficiency of the network, therefore the power distribution, intra-system interference maps and power delay profiles are calculated based on the simulation results. Finally, the validity of the simulation is proved comparing the obtained power level results and the RSSI level provided by WSN. The output of the proposed wireless systems planning process leads to energy efficient as well as to capacity enhanced network designs.
  • Open access
  • 61 Reads
Singular Value Decomposition Applied to Automatic Target Recognition with High Resolution Range Profiles
With the development of wideband radars new applications have emerged related to this kind of sensor. That is the case of automatic target recognition based on radar imagery. In this paper a target recognition methodology based on one dimensional high resolution radar imagery is presented. 1D radar images, namely high resolution range profiles (HRRP) are comprised of range bins and contain the distribution of the scattering centers of a target providing information about target structure. In this manuscript, identification of HRRP coming from measurements of in-flight aircraft is carried out by comparison with a database of simulated HRRPs. Simulated HRRPs have a very clean signature while actual HRRPs suffer from noise and other unwanted effects making the recognition process an arduous task. In order to overcome the differences between profiles, Singular Value Decomposition (SVD) is applied to matrices of HRRP. SVD is a robust tool for the decomposition of any matrix into orthogonal basis spaces, thus, by applying SVD to the HRRP matrices and selecting the most significant singular vectors, the matrices can be split into a signal and a noise subspace. The identification algorithm proposed in this paper is based on finding the aircraft which minimizes the angle between signal subspaces. Confusion matrices for the classification of the whole test set and error rates obtained will be provided in the paper full-version. As will be shown, the use of SVD provides good recognition rates even the lack of similarity between actual and simulated profiles.
  • Open access
  • 86 Reads
Screening of Bioluminescent Bacterial strains for evolution of Novel Toxicity Sensing Beads
In the present study, exploration of the diverse marine ecosystems of Dapoli beach, Kokan, Maharashtra, India (Asia) for possible isolation of novel bioluminescence bacterial species was undertaken. Further, these isolates were analysed for their potential use as a biological indicators. Preliminary isolation and screening of isolated bioluminescent bacteria was done by morphological & biochemical techniques.  Furthermore, the molecular characterization was accomplished by the 16s rDNA analysis. The 16S rDNA amplified genes was sequenced and sequences were analysed by BLAST for similarity search which confirmed that DM & DS designated isolates were Vibrio fischeri & Photobacterium phosphoreum respectively. Phylogenetic analysis was done with the aid of MEGA 4.0 software. Additionally, the lux genes were also amplified as a bioluminescent bacterial strain specific marker gene.Moreover, the biosensing capability of isolates was investigated against various forms of heavy metals & antibiotics. Correlating luminescence pattern of isolates against toxic pollutants generated during proposed investigations would be of great help to develop an efficient & rapid water pollution monitoring biosensor. Finally, these bacterial strains were immobilized in varied percentage of sodium alginate and concentrations of calcium chloride, respectively. 1% sodium alginate & 0.1M CaCl2 is found to be most appropriate immobilization material. Bioluminescent beads were tested against various toxic heavy metal compounds. These bioluminescent beads are reusable for atleast two times & would prove to be the secure, rapid, and responsive monitoring system which could detect a wide variety of heavy metal pollutants.
  • Open access
  • 100 Reads
Object-Based Feature Extraction of Google Earth Imagery for Mapping Termite Mounds in Amazon's Savannas
This study investigates the potential of object-based feature extraction from Google Earth Imagery for mapping termite mounds in Amazon's savannas. Termite mounds are often hotspots of plant growth (i.e. primary productivity). Accurate and timely information about termite mounds is crucial for land management decision-making and ecosystem monitoring. To address this issue, the effectiveness of object-based feature extraction that use automated image segmentation to extract meaningful ground features from imagery was tested. The study used very high resolution multispectral Google Earth images to produce termite mounds maps in Bahia, Brazil. The results from the study indicated that an object-based approach provides a better means for ground feature extraction than a pixel based method because it provides an effective way to incorporate spatial information and expert knowledge into the feature extraction process. Also the results suggest that Google earth imagery has considerable potential in mapping termite mounds in Amazon's savannas.
  • Open access
  • 64 Reads
Design and Optimization of Mach-Zehnder Interferometer Sensor for Dye Sensing by Using Central Composite Design Coupled with Surface Response Method
Color concentration detection is one of the main monitoring processes in textile industry. Highly sensitive sensors and less cumbersome procedure in monitoring color concentration are required. Potential for using fibre optics sensor in such measurement is promising because of its high sensitivity and fast response. In this study, concentration of Remazol Black B (RBB) dye solution was measured by using Mach-Zehnder interferometer (MZI) sensor with concatenating tapered multimode fibre (MMF) between two sections of single-mode fibre (SMF). The aim of this work is to study the interaction between the operating parameters, diameter of MMF and concentration of RBB dye solution. Central composite design (CCD) coupled with Response surface method (RSM) was applied to obtain optimum operating parameters for achieving well-responding operating variables, relative output intensity and wavelength shift. The proposed sensor was tested through additional experiments at optimum conditions (MMF with diameter of 19.5 µm; dye solution with concentration of 200ppm and corresponding wavelength of 1550nm). The difference between the experimental and modeled data was only less than 10% which showed good agreement between them. Knowledge of this optimization sensing conditions, it may be useful and attractive to detect the concentrations of many other chemical compounds in practical applications.
  • Open access
  • 113 Reads
A Novel MEMS based Surface Acoustic Wave Gas Sensor for Carbon Dioxide Detection in Hot-Process Areas
The ever increasing applications of sensor networks is causing a growth in demand for low cost, energy efficient sensors for monitoring physical environment such as temperature, gas concentration or pressure, especially in hot-process areas. The paper presents a 3D model of a Surface Acoustic Wave Gas sensor for detection of CO2 in high temperature areas. A robust and sensitive chemisensor has been realized by using the SAW phenomenon. In this study, nanostructures have been added in addition to the metallic layer to increase the surface to volume ratio of the sensor. The sensitivity of the sensor has been increased by using a piezoelectric material as a sensing layer. The choice of material absorption has been chosen by using Hard-Soft-Acid –Base theory, which is a relatively new concept to determine polymers for the active layer. The reliance of SAW reflection factor for unidirectional IDTs loaded by impedance on its resistive value was investigated, The sensor showed great results when exposed to varied concentrations of CO2 . Study also showed that langasite showed a stable frequency at higher temperature as compared to commonly used litium niobate. The design and simulation of the sensor is done using the Finite Element Analysis (FEA) module of COMSOL Multiphysics. The high temperature stability, fast response and robustness of the sensor showed promising industry applications.
  • Open access
  • 123 Reads
Micro-Raman Spectroscopy for Assessment of Periodontal Disease Follow-Up
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The aim of this study was to investigate the potentiality of the Micro-Raman spectroscopy in a follow up of the periodontal disease by performing a clinical not invasive sample collection method. Samples of gingival crevicular fluid (GCF) from informed periodontal and health patients were pooled. Specifically, the gingival crevicular fluid was collected with #30 standardized sterile absorbent paper cones inserted 1 mm into the gingival crevice and left in situ for 30 s [1]. The intra-oral clinical examinations were performed on one buccal site per maxillary central incisor. Each sample was tested by micro-Raman spectrometry. Raman spectra showed the presence of carotene in GCF periodontal patient's samples. With osteopotin, the carotene is expected to be correlates in crevicular fluid and salive with periodontal disease [2]. An automatic numerical data treatment based on wavelet algorithm was used in order to suppress the non-correlated signal, to subtract the background signal and to increase the quantitative readability of the Raman signal [3]. Micro-Raman spectroscopy is a very promising tool for medical applications, for its sensitivity to subtle changes in the chemical and structural characteristics of biological specimens [4]. [1] G. Perinetti, M. Paolantonio, B. Femminella, E. Serra, G. Spoto. G, J Periodontol 79 (2008) , 1200. [2] C.G. Sharma, A.R. Pradeep. J Periodont Res 42(2007) 450.[3] C. Camerlingo, F. Zenone, G.M. Gaeta, R. Riccio, M. Lepore. Meas Sci Technol 17 (2006) 298. [4] C. Camerlingo, F. Zenone, G. Perna, V. Capozzi, N. Cirillo, G.M. Gaeta, M. Lepore. . Sensors 8 (2008) 3656-64.
  • Open access
  • 68 Reads
Analysis of Radio Wave Propagation for ISM 2.4GHz Wireless Sensor Networks in Inhomogeneous Vegetation Environments
The use of wireless networks has been extended in an exponential growing due to the improvement in terms of battery life and low consumption of the devices. However, it is highly important to conduct previous radio propagation analysis when deploying a wireless sensor network. These studies are necessary to perform an estimation of the range coverage, in order to optimize the distance between devices in an actual network deployment. In this work, the radio channel characterization for ISM 2.4GHz Wireless Sensor Networks (WSN) in an inhomogeneous vegetation environment has been analyzed. The impact of topology as well as morphology of the environment is assessed by means of an in-house developed 3D Ray Launching code, to emulate the realistic operation in the framework of the scenario. Experimental results gathered from a measurements campaign conducted by deploying a ZigBee Wireless Sensor Network, are analyzed and compared with simulations in this paper. The scenario where this network is intended to operate is a combination of buildings and diverse vegetation species. To gain insight in the effects of radio propagation, a simplified vegetation model has been developed, considering the material parameters and simplified geometry embedded in the simulation scenario. The use of deterministic tools can aid to know the impact of the topological influence in the deployment of the optimal Wireless Sensor Network in terms of capacity, coverage and energy consumption, making the use of these systems attractive for multiple applications in inhomogeneous vegetation environments.