Data Acquisition Stage Research Articles

Disentangling white-matter damage from physiological fibre orientation dispersion in multiple sclerosis.

Multiple sclerosis leads to diffuse damage of the central nervous system, affecting also the normal-appearing white matter. Demyelination and axonal degeneration reduce regional fractional anisotropy in normal-appearing white matter, which can be routinely mapped with diffusion tensor imaging. However, the standard fractional anisotropy metric is also sensitive to physiological variations in orientation dispersion of white matter fibres. This complicates the detection of disease-related damage in large parts of cerebral white matter where microstructure physiologically displays a high degree of fibre dispersion. To resolve this ambiguity, we employed a novel tensor-valued encoding method for diffusion MRI, which yields a microscopic fractional anisotropy metric that is unaffected by regional variations in orientation dispersion. In 26 patients with relapsing-remitting multiple sclerosis, 14 patients with primary-progressive multiple sclerosis and 27 age-matched healthy controls, we compared standard fractional anisotropy mapping with the novel microscopic fractional anisotropy mapping method, focusing on normal-appearing white matter. Mean microscopic fractional anisotropy and standard fractional anisotropy of normal-appearing white matter were significantly reduced in both patient groups relative to healthy controls, but microscopic fractional anisotropy yielded a better reflection of disease-related white-matter alterations. The reduction in mean microscopic fractional anisotropy showed a significant positive linear relationship with physical disability, as reflected by the expanded disability status scale. Mean reduction of microscopic fractional anisotropy in normal-appearing white matter also scaled positively with individual cognitive dysfunction, as measured with the symbol digit modality test. Mean microscopic fractional anisotropy reduction in normal-appearing white matter also showed a positive relationship with total white-matter lesion load as well as lesion load in specific tract systems. None of these relationships between normal-appearing white-matter microstructure and clinical, cognitive or structural measures emerged when using mean fractional anisotropy. Together, the results provide converging evidence that microscopic fractional anisotropy mapping substantially advances the assessment of cerebral white matter in multiple sclerosis by disentangling microstructure damage from variations in physiological fibre orientation dispersion at the stage of data acquisition. Since tensor-valued encoding can be implemented in routine diffusion MRI, microscopic fractional anisotropy mapping bears considerable potential for the future assessment of disease progression in normal-appearing white matter in both relapsing-remitting and progressive forms of multiple sclerosis as well as other white-matter-related brain diseases.

Three-dimensional angle-domain double-square-root migration in VTI media for the large-scale wide-azimuth seismic data

With the development of oil and gas exploration, the conventional seismic migration imaging technology based on the isotropic assumption no longer meets our current requirements for high-resolution images. Migration in anisotropic media has become an essential requirement for oil and gas exploration. Marine seismic exploration has gradually entered the wide-azimuth and high-density seismic data acquisition stage. However, even for current large high-performance computer clusters, it is still very difficult to implement pre-stack depth migration based on shot gathers. Thus, we present a double-square-root (DSR) equation based on three-dimensional (3D) pre-stack depth migration in midpoint-offset domain for a wide-azimuth dataset in transversely isotropic media with a vertical symmetry axis (VTI media). Considering VTI media, the DSR migration requires extensive memory and computation; we adopted the phase-shift plus interpolation approach to improve the computational efficiency. Then, we extract the angle-domain common-image gathers (ADCIGs) during DSR migration. For real large-scale seismic data, we designed an effective parallel implementation of 3D DSR migration with ADCIGs outputs. Finally, we applied the proposed angle-domain VTI DSR migration on wide-azimuth SEG/EAGE salt dome-based data and real data from the China South Sea. Numerical and practical data illustrate the effectiveness of the proposed method.

Ground-penetrating radar data diffraction focusing without a velocity model

Ground-penetrating Radar (GPR) sections commonly suffer from strong scattered energy and weak reflectors with distorted lateral continuity. This is mainly due to the gradual variation of moisture with depth, dense lateral sampling of common-offset GPR traces (which are considered as zero-offset data), along with the small wavelength of the electromagnetic waves that is comparable to the size of the shallow subsurface dielectric heterogeneities. Focusing of the diffractions requires efficient migration that, in the presence of highly heterogeneous subsurface formations, can be improved by a detailed migration velocity model. Such a velocity model is difficult to develop because the common-offset antenna array is mostly used for its reduced time and cost in the data acquisition and processing stages. In such cases, migration processes are based on limited information from velocity analysis of clear diffractions, cores, or other ground truth knowledge, often leading to insufficient imaging. We have developed a methodology to obtain GPR sections with focused diffractions that is based on multipath summation, using weighted stacking (summation) of constant-velocity migrated sections over a predefined velocity range. The success of this method depends on the assignment of an appropriate weight, for each constant-velocity migrated section to contribute to the final stack, and the optimal width of the velocity range used. Additionally, we develop a postmultipath summation processing step, which consists of time-varying spectral whitening, to deal with the decrease of the dominant frequency due to attenuation effects and the additional degraded resolution expected by the constant migration summed images. This imaging strategy leads to GPR sections with sufficiently focused diffractions, enhancing the lateral and the temporal resolution, without the need to explicitly build a migration velocity model.

Research and Design of Field and Office Work Integration System for Historical Buildings Conservation: Case Study on Guangzhou

In recent years, GIS-based technologies has been applied in multiple fields of study, including historical building conservation. In the field of historic building conservation, GIS technology is mainly used for the spatial information display and spatial analysis of buildings. In terms of traditional methods of historical buildings information collection, GIS technology is mainly applied in the functions of data warehousing and statistical analysis, but barely in the early stage of data acquisition. This article introduces the technology of historical building information acquisition based on mobile GIS device, as well as the integrated data acquisition system, which changes the pattern that separates field and office work. The field collected data is directly imported into the data processing system on the basis of unified data standard, which shortens the intermediate link and integrates the field and office work. As a result of the improved pattern, the efficiency of historical building conservation will be significantly increased.

Excessive data collection: Privacy considerations and abuse of dominance in the era of big data

The present era of big data challenges many of the basic assumptions of competition law. One particularly pressing question is: to what extent should privacy considerations and data protection filter into competition law assessments? The paper focuses on personalized user data that companies gather through third-party tracking on the web. This practice allows the tracker to build comprehensive user profiles across platforms and devices, placing an unprecedented volume of up-to-date personal data in the hands of a small number of globally active companies. Focusing on the stage of data acquisition, the paper assesses two scenarios under which EU competition law may deem the vast amounts of data gathered by certain digital platforms excessive under Article 102(a) TFEU: excessive data “prices” and data policies as unfair trading conditions. In both cases, the competition law assessment is autonomous from other areas of the law: while a breach of data protection rules is not automatically a breach of competition law, a company adhering to data protection rules may still violate competition laws. The paper finds that EU competition law already possesses the necessary tools to address excessive data collection, while data protection rules provide much-needed context for this type of exploitative abuse.

Underwater Photogrammetry Application for Coral Reef Mapping and Monitoring

Underwater 3D reconstruction techniques such as underwater photogrammetry are the latest trend in low cost survey techniques. This article explains how the data acquisition process is up to the process of producing an underwater photo map. Automatic data processing for coral reef objects from the initial data acquisition stage to building 3D models from seabed objects to rendering in virtual reality. In this paper, underwater photogrammetry was applied with SfM (Structure from Motion) algorithm in performing 3D reconstruction of coral reefs that will be produce orthophoto map. Geodetic measurements also performed to the model for control point. The analysis will be divided into t-test and F-test. From the processing, coral reef modeling has obtained the result of a linear error which t-test produce <50% data, both at 95% and at 99 % confidence level. The F-test gain a positive value where the point value used in the linear error test on marker L and K, the value at α = 0.05. The 3D coral reef model in the resulting orthophoto still has weaknesses, for example the color appearance that depends on the level of clarity of the water as well as the camera filter used. However, in 2D display is sufficient and can be an alternative to other methods, for example, the LIT method.

МАТЕМАТИЧНА МОДЕЛЬ ВИКОНАННЯ ВОГНЕВИХ ЗАДАЧ ЕКІПАЖЕМ ТАНКА НА ПОЛІ БОЮ

Reconnaissance and defeat of enemy targets on the battlefield depends on the technical characteristics of surveillance and sighting devices, and it is important to ensure their effective operation, during both the day and night, especially in adverse weather conditions. Therefore, in the field of modernization and development of surveillance and sighting devices, by both domestic and foreign manufacturers, in recent years there has been a major trend towards the development of multi-channel sighting systems on armored vehicles. To determine the optimal parameters of the sighting systems of armored vehicle samples, it is necessary to develop a mathematical model that would take into account the entire process of target reconnaissance, including the impact of full range of natural and man-made obstacles, to determine the ways for the improvement of combat effectiveness of weapons samples. In this work, a mathematical model is developed for description of fire tasks execution on the battlefield by a tank crew, which is equipped with a multi-channel sight-monitoring system, to assess the work of the sighting system as whole as well as of each of its channels. The analysis of the functional scheme of solving the combat task shows that the stage of data acquisition should be divided into, at least three, separate states, namely: detection, recognition and identification such that the transitions between these states will be described by the corresponding probabilities. The developed model describes the sequence of events that in terms of probability theory form a Markov chain. The proposed analytical Markov model allows for modeling the solution of fire tasks by the tank crew equipped with a multi-channel sighting and observation system with separate consideration of the stages of target reconnaissance, its recognition and identification, which in turn are considered as separate states of the Markov chain. The model opens a possibility for the development of an extended model to determine a quantitative indicator to assess the effectiveness of a given sighting system in comparison with its analogs.

Correspondence Matching and Time Delay Estimation for Hand-eye Calibration

For visually aided industrial robots, the transformation between the mounted visual information system and the end-effector must be calibrated prior to the practical use. However, during the data acquisition stage, measurement uncertainties will lead to inevitable mismatched data. This article proposes a novel correspondence matching method for the hand-eye calibration system of the type $\boldsymbol {AX} = \boldsymbol {XB}$ . The correspondence matching refers to the problem of finding out the well-matched $\boldsymbol {A}$ and $\boldsymbol {B}$ and the relative time delay between them, from a series of measurements. A neat Lie algebra formulation has been obtained to cast the original problem into a high-dimensional point-cloud registration problem. This solution allows for the simultaneous solution of the hand-eye calibration, correspondence matching, and time-delay estimation as well as the uncertainty description of the obtained results. Synthetic simulations verify the correctness of the proposed method. Experimental studies have also confirmed its practical feasibility on an automatic welding platform.

Examining Naturogenic Processes and Anthropogenic Influences on Tree Growth and Development via Stem Analysis: Data Processing and Computational Analytics

The objective of this study was to develop a stem analysis data processing and computational algorithm and associated software suite that was (1) applicable to temperate and boreal forest tree species, (2) mathematically consistent with excurrent tree stem geometric and allometric principles, (3) compatible with data structures obtained using proprietary and non-proprietary imaging systems, and (4) executable on Windows®-based operating systems. Computationally, the suite denoted SAP (Stem Analysis Program), deployed sectional-specific formulae that were in accord with the following geometric assumptions: (1) stump section was treated as a solid of revolution resembling a cylinder; (2) sections between the stump and the tip were treated as a solid of revolution resembling a frustum of a cone for sections with continuous annual increments, otherwise treated as a cone; and (3) tip section was treated as a solid of revolution resembling a cone. The algorithm also corrected for the slant-based sectional length measurements using Pythagorean Theorem and eliminated the requirement to predict age-specific apex height development through the use of a linear interpolation procedure. Based on input data structures consisting of annual ring-width xylem sequences measured from cross-sectional disk samples acquired at multiple positions along the tree’s main stem, the suite produces a broad array of output, inclusive of radial and longitudinal ring-width sequences, apical growth increments, annual and cumulative sectional and cumulative volume production patterns, and historically reconstructed stem taper profiles. In total, the SAP creates six output data files for each tree analyzed: (1) input data reference summary (e.g., geometric mean ring-widths and resultant radii for each cross-section); (2) radial growth patterns for the cross-section sampled at breast-height (e.g., absolute and relative diameter and basal area growth estimates); (3) sectional (vertical) profiles of volume growth patterns (e.g., absolute and relative growth estimates within each section (bolt)); (4) cumulative volume growth patterns for the entire tree; (5) historical taper profile estimates (e.g., heights and diameters by year); and (6) texturally-labeled compendium of all output files generated. Additionally, real-time graphical output was produced for the purposes of data assessment and verification during the radial sequence data acquisition stage (e.g., graphical presentation of annual ring-width sequences by radii and disk, for use in validating input data structures and increment measurements derived from the imaging system), and interpreting growth and development patterns (e.g., vertical growth layer and specific volume increment profiles by age or year). The utility of the SAP suite was exemplified by processing WindendroTM-based annual ring-width xylem sequences obtained from cross-sectional disks extracted from a jack pine (Pinus banksiana Lamb.) tree via percent-height destructive stem analysis, and subsequently elucidating growth and developmental patterns within the context of silviculture treatment effects (thinning). The SAP suite provides the conceptual and logistical foundation for the continued deployment of the stem analysis approach in a wide range of investigations, including those examining the effect of naturogenic processes and anthropogenic influences on tree growth and development.

Impact of Physiological Signals Acquisition in the Emotional Support Provided in Learning Scenarios.

Physiological sensors can be used to detect changes in the emotional state of users with affective computing. This has lately been applied in the educational domain, aimed to better support learners during the learning process. For this purpose, we have developed the AICARP (Ambient Intelligence Context-aware Affective Recommender Platform) infrastructure, which detects changes in the emotional state of the user and provides personalized multisensorial support to help manage the emotional state by taking advantage of ambient intelligence features. We have developed a third version of this infrastructure, AICARP.V3, which addresses several problems detected in the data acquisition stage of the second version, (i.e., intrusion of the pulse sensor, poor resolution and low signal to noise ratio in the galvanic skin response sensor and slow response time of the temperature sensor) and extends the capabilities to integrate new actuators. This improved incorporates a new acquisition platform (shield) called PhyAS (Physiological Acquisition Shield), which reduces the number of control units to only one, and supports both gathering physiological signals with better precision and delivering multisensory feedback with more flexibility, by means of new actuators that can be added/discarded on top of just that single shield. The improvements in the quality of the acquired signals allow better recognition of the emotional states. Thereof, AICARP.V3 gives a more accurate personalized emotional support to the user, based on a rule-based approach that triggers multisensorial feedback, if necessary. This represents progress in solving an open problem: develop systems that perform as effectively as a human expert in a complex task such as the recognition of emotional states.

To reduce or not to reduce: a study on spatio-temporal surveillance

The majority of control charts based on scan statistics for spatio-temporal surveillance use full observation vectors. In high-dimensional applications, dimension-reduction techniques are usually applied. Typically, the dimension reduction is conducted as a post-processing step rather than in the data acquisition stage and thus, a full sample covariance matrix is required. When the dimensionality of data is high, (i) the sample covariance matrix tends to be ill-conditioned due to a limited number of samples; (ii) the inversion of such a sample covariance matrix causes numerical issues; and (iii) aggregating information from all variables may lead to high communication costs in sensor networks. In this paper, we propose a set of reduced-dimension (RD) control charts that perform dimension reduction during the data acquisition process by spatial scanning. The proposed methods avoid computational difficulties and possibly high communication costs. We derive a theoretical measure that characterizes the performance difference between the RD approach and the full observation approach. The numerical results show that the RD approach has little performance loss under several commonly used spatial models while enjoying all the benefits of implementation. A case study on water quality monitoring demonstrates the effectiveness of the proposed methods in real applications.

Visualizing intrusions in dynamic building environments for worker safety

A review of the existing literature suggests that intrusions on sites are often overlooked as current construction safety assessment methods are primarily focused on visible consequences such as injuries and deaths. Moreover, traditional Behavior-Based Safety (BBS) methods for improving worker attitude towards adopting safety practices on work sites are not adequate as these methods do not provide quick feedback for changing unsafe worker behaviors in real-time to avoid fatalities. Consequently, geo-localization systems are used for acquiring spatio-temporal trajectories to identify unsafe worker behaviors on construction sites. However, spatio-temporal trajectories lack contextual building or site information. For incorporating the geographical and application-specific context in trajectories, semantic enrichment processes are executed. The semantic enrichment process should include changing contextual information related to the evolving building objects over time. The changing contextual information of building objects is required to be tracked by a system to study the worker behaviors in a dynamic building environment context. After reviewing the existing literature, it is concluded that none of the present systems offer a mechanism to identify unsafe worker behaviors such as intrusions in dynamic environments where the contextual information of building spaces evolves over time in terms of location, size, properties and relationships with the environment. To fill this research gap, a system is proposed; First, to acquire the worker movements using Bluetooth Low Energy (BLE) beacons. Second, to perform the pre-processing as well as semantically enriching the spatio-temporal worker trajectories using relevant updated contextual information of a building. Lastly, to visualize the building locations where intrusions have occurred using Building Information Modeling (BIM) approach. The developed system presents an integration of systems from the data acquisition stage to visualizing the unsafe work behaviors that could serve as a foundation for future research in studying advanced movement-related worker behaviors in dynamic environments by overcoming the spatio-temporal data management challenges.

Optimization-based gravity-assisted calibration and axis alignment of 9-degrees of freedom inertial measurement unit without external equipment

Applicable in numerous fields, low-cost micro-electromechanical system inertial measurement units often require on-sight calibration by the end user due to the existence of systematic errors. A 9-degrees of freedom inertial measurement unit comprises a tri-axis accelerometer, a tri-axis gyroscope, and a tri-axis magnetometer. Various proposed multi-position calibration methods can calibrate tri-axis accelerometers and magnetometers to a degree. Yet the full calibration of a tri-axis gyroscope and axis alignment of all the sensors still often requires equipment such as a rate table to generate a priori known angular velocities and attitudes or relies on the disturbance-prone magnetometer output as a reference. This study proposes an augmentation to the popular multi-position calibration scheme, capable of fully calibrating and aligning the sensor axes of the 9-degrees of freedom inertial measurement unit while eliminating the reliance on external equipment or magnetometer. The algorithm does not rely on the inertial measurement unit attitude during various stages of the multi-position data acquisition. Instead, it uses the gravity vector measured by the accelerometer to calibrate the gyroscope and align the magnetometer axes with the sensor body frame. Experimental results using a navigation module with factory calibration and extensive simulation results indicate the current method's ability in estimating large calibration parameters with relative errors below 0.5%.

Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender

<p class="Abstract"><em><span>Good mental health is important in our daily life. A person commonly finds stress as a barrier to enhance an individual’s performance. Be reminded that not all people have the same level of stress because different people have dissimilar problems in their life. In addition, different level of age and gender will affect unequal amount of stress. Electrocardiogram (ECG) signal is an electrical indicator of the heart that can detect changes of human response which relates to our emotions and reactions. Thus, this research proposed a non-intrusive detector to identify stress level for both gender and different classification of age using the ECG. A total of 30 healthy subjects were involved during the data acquisition stage. Data acquisition which initialize ECG data were divided into two conditions; which are normal and stress states. ECG data for normal state only need the participant to breath in and out normally. In other hand, the participants also need to undergo Stroop Colour word test as a stress inducer to represent ECG in stress state. Then, Sgolay filter was selected in the pre-processing stage to remove artifacts in the signal. The process was followed by feature extraction of the ECG signal and finally classified using RR Interval (RRI), different amplitudes of R peaks and Cardioid graph were used to evaluate the performance of the proposed technique. As a result, Class 5 (age range between 50-59 years old) marks the highest changes of stress level rather than other classes, while women are more affected by stress rather than men by showing tremendous percentage changes between normal and stress level over the proposed classifiers. The result proves that ECG signals can be used as an alternative mechanism to recognize stress more efficiently with the integration of gender and age variabilities.</span></em></p>

Artificial vision assisted ground fine pointing system for experimental optical link for CubeSat communications

Considering the continuous increase of demands in satellite communications, it is imperative to determine systems with higher bandwidths. Furthermore, miniaturization trends coming from the development of nanosatellites as CubeSat’s, constitute great restrictions to their design. Optical communications have the potential to lead with current data rates requirements. Nevertheless, the establishment of ground-LEO (Low Earth Orbit) optical links poses several challenges such as very strict and accurate tracking mechanisms, effects provoked due to the environmental conditions on the light beam as well as attenuation and Doppler effects. In this work, the precision of the tracking mechanisms is tackled by employing artificial vision as a proposal for a fine tracking system for an optical ground station to be able to locate a LEO CubeSat, so to proceed with data acquisition and tracking stages. The innovative and highly efficient algorithm herein developed for fine pointing is implemented in LabVIEW® as an example.

Combined Close Range Photogrammetry and Terrestrial Laser Scanning for Ship Hull Modelling

The paper addresses the fields of combined close-range photogrammetry and terrestrial laser scanning in the light of ship modelling. The authors pointed out precision and measurement accuracy due to their possible complex application for ship hulls inventories. Due to prescribed vitality of every ship structure, it is crucial to prepare documentation to support the vessel processes. The presented methods are directed, combined photogrammetric techniques in ship hull inventory due to submarines. The class of photogrammetry techniques based on high quality photos are supposed to be relevant techniques of the inventories’ purpose. An innovative approach combines these methods with Terrestrial Laser Scanning. The process stages of data acquisition, post-processing, and result analysis are presented and discussed due to market requirements. Advantages and disadvantages of the applied methods are presented.

Online radio interferometric imaging: assimilating and discarding visibilities on arrival

The emerging generation of radio interferometric (RI) telescopes, such as the Square Kilometre Array (SKA), will acquire massive volumes of data and transition radio astronomy to a big-data era. The ill-posed inverse problem of imaging the raw visibilities acquired by RI telescopes will become significantly more computationally challenging, particularly in terms of data storage and computational cost. Current RI imaging methods, such as CLEAN, its variants, and compressive sensing approaches (sparse regularisation), have yielded excellent reconstruction fidelity. However, scaling these methods to big-data remains difficult if not impossible in some cases. All state-of-the-art methods in RI imaging lack the ability to process data streams as they are acquired during the data observation stage. Such approaches are referred to as online processing methods. We present an online sparse regularisation methodology for RI imaging. Image reconstruction is performed simultaneously with data acquisition, where observed visibilities are assimilated into the reconstructed image as they arrive and then discarded. Since visibilities are processed online, good reconstructions are recovered much faster than standard (offline) methods which cannot start until the data acquisition stage completes. Moreover, the online method provides additional computational savings and, most importantly, dramatically reduces data storage requirements. Theoretically, the reconstructed images are of the same fidelity as those recovered by the equivalent offline approach and, in practice, very similar reconstruction fidelity is achieved. We anticipate online imaging techniques, as proposed here, will be critical in scaling RI imaging to the emerging big-data era of radio astronomy.

Maximising BOLD sensitivity through automated EPI protocol optimisation

Gradient echo echo-planar imaging (GE EPI) is used for most fMRI studies but can suffer substantially from image distortions and BOLD sensitivity (BS) loss due to susceptibility-induced magnetic field inhomogeneities. While there are various post-processing methods for correcting image distortions, signal dropouts cannot be recovered and therefore need to be addressed at the data acquisition stage. Common approaches for reducing susceptibility-related BS loss in selected brain areas are: z-shimming, inverting the phase encoding (PE) gradient polarity, optimizing the slice tilt and increasing spatial resolution. The optimization of these parameters can be based on atlases derived from multiple echo-planar imaging (EPI) acquisitions. However, this requires resource and time, which imposes a practical limitation on the range over which parameters can be optimised meaning that the chosen settings may still be sub-optimal. To address this issue, we have developed an automated method that can be used to optimize across a large parameter space. It is based on numerical signal simulations of the BS loss predicted by physical models informed by a large database of magnetic field (B0) maps acquired on a broad cohort of participants. The advantage of our simulation-based approach compared to previous methods is that it saves time and expensive measurements and allows for optimizing EPI protocols by incorporating a broad range of factors, including different resolutions, echo times or slice orientations. To verify the numerical optimisation, results are compared to those from an earlier study and to experimental BS measurements carried out in six healthy volunteers.

Phase II monitoring of free-form surfaces: An application to 3D printing

Three-dimensional (3D) printing techniques have become popular in recent years. Monitoring the quality of its products is thus important. In the literature, there is little existing research on this topic now, partly because it is a challenging problem with complex data structures. In this article, we propose a nonparametric control chart for Phase II monitoring of the top surfaces of 3D printing products. The top surfaces are focused in this article because they are our major concern regarding the quality of 3D printing products in some applications. Such surfaces are often free-form surfaces. Our proposed method is based on local kernel estimation of free-form surfaces. Before Phase II monitoring, observed data from different products are first geometrically aligned to account for possible movement between the products and a laser scanner during the data acquisition stage. Numerical studies show that the proposed method works well in practice.

ANALYSIS AND DEVELOPMENT OF A SOLAR COLLECTOR USING CELLULAR ALVEOLAR POLYCARBONATE FOR ECOLOGICAL AND LOW TEMPERATURE WATER HEATING SYSTEMS

This article presents the analysis and development of a new alternative for ecological heaters based on cellular polycarbonate with eight millimeters of thickness as a flat solar collector without cover. The analysis is developed in a simple system which comprises two solar collectors and an automatic data acquisition stage that periodically provides the meteorological and system data of one month. For determining the utility and applicability of this type of solar collector, a comparison with a black body polycarbonate is performed. The resulting experimental data allows carrying out an energetic comparative analysis with respect to a commercial solar collector without a cover.