Wyniki 1-10 spośród 10 dla zapytania: authorDesc:"Grzegorz KŁOSOWSKI"

EIT detection methods of damage in landfills and flood embankments DOI:10.15199/48.2019.05.13

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The presented article describes a group of innovative methods enabling the identification of damage to landfills and flood embankments. These are methods based on electrical impedance tomography (EIT) [1], however, significantly improved by using original algorithms that enable reconstruction of tomographic images. In this study, three types of hybrid algorithms were considered:  generalized linear regression (GLR) [2],  generalized linear regression with stepwise regression (GLR-SR),  ElasticNET [3]. All three of the above statistical methods were used to reduce the number of predictors. In the considered EIT system, the input vector consists of 192 values of voltage drops taken due to the arrangement of 16 electrodes. The input vector reduced in this way was further used to train the artificial neural networks system (ANN) [4]. Among the tomographic methods, apart from the EIT, one can also be distinguished: electrical capacitance tomography [5-9], magnetoacoustics [10], multipath tomography [11] and others. In order to improve the imaging quality, various methods are used, mostly based on modern information techniques: fuzzy logic [12], GPU parallel computing [13], integer linear programming [14], etc. Flood is one of the most common and frequent natural disasters. Floods are the cause of many human dramas. One of the ways to protect the floodplains near landfills, rivers and water banks is to lift flood embankments. Thanks to this, you can temporarily raise the level of freshet over the main river bed and suppress the flood. However, higher water level accelerates the erosion of the top of the embankment or landfill barrier and can destroy it. In addition, given the insufficient filtration power of the embankment body, high water can lead to an increase in the number of leaks, which may lead to partial destruction of the flood bank. Despite significant achievements in the design of safe bunds[...]

The use of elastic net and neural networks in industrial process tomography DOI:10.15199/48.2019.05.15

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Industrial Process Tomography (IPT) is a non-invasive and non-destructive imaging [1] technique used in various industries for processes in which knowledge about the interior of the object is required [2], [3]. A common reason for using IPT is that it plays an important role in the continuous monitoring of systems, allowing better understanding and ensuring the quality of industrial processes. IPT provides fast and dynamic response, facilitates process control, including on-line, enables error detection and system failures in real time [4]. In addition, thanks to IPT, the process characteristics can be quantified, with data included in the overall process control strategy. Finally, IPT provides robust experimental means to optimize the design and operation of a process tank or pipeline by developing a model and validation. Industrial process tomography (IPT) applications are usually a challenge for obtaining spatial data from observation beyond the boundaries of the process. The wireless sensor network technology with their return loops will be the basis for production control. The decisive difference in mass production of chemicals, metals, building materials, food and other goods is that common process sensors provide only local measurements such as temperature, pressure, fill level, flow rate or species concentration. However, in most production systems, such local measurements are not representative of the overall process and therefore spatial solutions are needed. Here the future belongs to the dispersed and imaging sensors. The tomograph can be adapted to the requirements of a given company and to the specifics of a given industry. The prepared solution can effectively support the quality of products in automated production lines by identifying shapes, detecting cracks and damage, and presenting three-dimensional visualization of industrial processes. This is especially important for dairy producers, where the foami[...]

Wykorzystanie nietypowych surowców i odpadów spożywczych w gorzelnictwie rolniczym (cz. I)

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W pracy przedstawiono wyniki badań mających na celu sprawdzenie możliwości wykorzystania do produkcji spirytusu surowego nietypowych surowców oraz odpadów spożywczych. Do badań wykorzystano ziarno sorgo i amarantusa oraz bulwy topinamburu (Albik, Rubik) i odpadowe orzechy włoskie. Badania prowadzono w skali laboratoryjnej. Fermentacje przy użyciu drożdży As-4 przebiegały bez zakłóceń. Mała zawartość substancji redukujących w wywarach, tj. od 0,1 do 0,4%, świadczy o dobrym wykorzystaniu cukrów w czasie fermentacji. Małą zawartością zanieczyszczeń chemicznych charakteryzowały się spirytusy surowe (poniżej lub niewiele przekraczające PN dla spirytusu zbożowego) otrzymane z ziarna sorgo, amarantusa oraz bulw topinamburu. Ze względu na dużą zawartość zanieczyszczeń (przekraczającą kilkakrotnie PN) spirytusy otrzymane z odpadowych orzechów włoskich nie nadają się do celów spożywczych. Z przeprowadzonych badań wynika, że atrakcyjnymi surowcami alternatywnymi, które mogą być wykorzystane do produkcji spirytusów surowych w gorzelniach rolniczych jest sorgo, amarantus i topinambur. Zagospodarowanie odpadów w postaci przeterminowanych orzechów włoskich należy rozpatrywać wyłącznie jako dodatek do przerobu innych surowców skrobiowych. W gorzelnictwie rolniczym poszukuje się surowców tanich, zawierających węglowodany podlegające fermentacji bezpośrednio lub po uprzedniej hydrolizie do cukrów prostych. Ze względu na niestabilność cen rynkowych głównych surowców gorzelniczych, takich jak: żyto, pszenżyto, kukurydza, ziemniaki itp., gorzelnicy poszukują surowców alternatywnych, które okresowo zapewnią ciągłość produkcji, przy jednoczesnej jej opłacalności. Dlatego w gorzelniach rolniczych w takiej sytuacji do produkcji spirytusu wykorzystywane są surowce odpadowe, przeterminowane. W praktyce do produkcji spirytusu można użyć każdy surowiec, w skład którego wchodzą monosacharydy i disacharydy w ilości gwarantującej opłacalność ekonomiczną procesu. S[...]

Wykorzystanie nietypowych surowców i odpadów spożywczych w gorzelnictwie rolniczym (cz. II*)

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W przeprowadzonych badaniach laboratoryjnych wykorzystano ziarno sorgo i amarantusa oraz bulwy topinamburu (Albik, Rubik) i odpadowe orzechy włoskie. Tabela 2 przedstawia charakterystykę podstawowych parametrów stosowanych w badaniach surowców oraz sporządzonych z ich wykorzystaniem zacierów słodkich. Największą wilgotnością charakteryzowały się topinambur biały (77%) i fioletowy (78%), a najmniejszą odpadowe orzechy włoskie (5,5%). Orzechy włoskie charakteryzowały się wysoką zawartością tłuszczu (61,6 %), natomiast zawartość węglowodanów była bardzo mała. Ekstrakt otrzymanych zacierów słodkich zawierał się w granicach od 18,1 oBlg (zacier z sorgo) do 7,6 oBlg (zacier z orzechów włoskich). Wartości pH tych zacierów były zbliżone i wynosiły od 5,6 (zacier z sorgo) do 5,4 (zacier z amarantusa). Fermentacje analizowanych surowców przy użyciu drożdży As-4 przebiegały bez zakłóceń. Po 72 h fermentacji (tabela 3) odfermentowanie pozorne wynosiło 0,3 oBlg (sorgo); 3,7 oBlg (topinambur Rubik); 3,5 oBlg (topinambur Albik); 4,5 oBlg (orzechy włoskie); 1,0 oBlg (amarantus). Badania mikroskopowe oraz wartości pH uzyskane po trzeciej dobie fermentacji, tj. od 4,7 do 4,3 - wskazują na brak infekcji bakteryjnych w zacierach. Zakażenie zacierów bakteriami powoduje bowiem wzrost kwasowości, co skutkuje spadkiem pH, nawet poniżej wartości 3,5. Stężenie alkoholu w zacierach z sorgo, topinamburu Rubik, topinamburu Albik, orzechów włoskich i amarantusa rosło odpowiednio od 3,47%, 2,85%, 2,85%, 1,93%, 7,12% (po 24 h) do 9,05%, 4,30%, 4,37%, 2,37, 8,57% (po 72 h). Największą wydajność etanolu ze 100 kg skrobi uzyskano w wyniku fermentacji amarantusa, tj. 66,38 dm3 A100/100 kg skrobi i sorgo, tj. 65,29 dm3 A100/100 kg skrobi. Produktywność fermentacji (cm3 A100/dm3 x h) była największa po pierwszej dobie i wynosiła odpowiednio: 1,44; 1,2; 1,2; 0,8; 2,96 cm3 A100/dm3 x h. Ubytek największej ilości CO2 stwierdzono po 72 h (rys. 8), przy fermentacji zacie[...]

Implementation of the LARS method to solve the inverse problem in electrical tomography DOI:10.15199/48.2018.12.31

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The tomographic method makes it possible to obtain moisture distribution inside the wall in a digital form. This is extremely useful when you need to obtain a high quality image in a non-invasive way. Visualization of the moisture inside the wall enables the implementation of effective protection of walls against moisture and in the case of old buildings - effective and fast drainage of walls. This is of particular importance for thick walls. The most important advantages of the proposed measurement system include non-invasive and non-destructive measurement of the tested object thanks to specially designed surface electrodes and the ability to display the moisture distribution inside the wall both on the plane (2D) and spatially (3D). Due to the fact that wall conductivity depends mainly on the degree of humidity, it is possible to determine the distribution of moisture inside the wall using the indirect method - based on the conductivity map. In the case of brick walls, this is the only cheap and non-invasive method, unlike the weight method, in which the wall must be drilled, and the heat generated evaporates a certain amount of moisture. This is, therefore, an invasive method of quality, not a quantitative method, thus subject to an additional error. We are interested only in differential (relative) images, on which we can distinguish specific colors from a dry background. Thanks to this, moisture content can be assessed in the tested cross-sections of walls or bricks. There are many different methods to optimize the solution mentioned above. problem [8-14,22,23]. This article presents the method of using the smallest angle algorithm [4] to solve the inverse problem in electrical tomography for damp wall [1-3,5-7,15-21]. Statistical method Reduction of adverse effects of multi-polarization between predictors can be achieved by applying the lowest angle regression algorithm for this solution. The algorithm in question [...]

The concept of the technological process control using a distributed industrial tomography system DOI:10.15199/48.2018.12.36

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Industrial tomography enables non-invasive, dynamic observation of physical and chemical phenomena without the need of mechanical interference into the interior of the investigated object [1-14,16,19-22]. Thanks to the features mentioned above, this type of tomography is ideal for automatic optimization of design and production processes. Process tomography systems can operate autonomously in the field of monitoring, measurement and control of the correct functioning of industrial processes. A network of sensors connected to the system provides a constant data flow enabling tracking of technological processes even in closed technical facilities, such as fermenters. Process tomography is also used to acquire data on the flow of fluids and loose components in pipelines that act as transport media [24-29, 31-37]. The data obtained from the sensors are delivered to the data warehouse, where they are further processed. As a consequence, data warehouses enable building a knowledge base on operating systems and processes. Data analysis results can be displayed in a suitable form on the monitor screen. In semi-automatic systems they can be used by the operator as elements of supporting decision-making processes, and in automatic systems, decisions are made by IT systems, and the information about the history of these decisions is a log file. The production process control tasks carried out in this way allow increasing the efficiency and quality of products, as well as increasing the company's competitiveness level. Methods of analysis and control of processes include issues related to the processing of data obtained from various sensors located in remote nodes. Monitoring is based on acquired and processed data due to appropriately elaborated algorithms for parameter automation [15,17,18,23,30,38]. This paper concerns the issues of processes control in a cyber-physical system based on the concept of a production process managemen[...]

Monitoring of flood embankments with the use of tomographic systems with distributed architecture DOI:10.15199/48.2018.12.37

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The disaster of the flood embankment often results in large economic and social losses, as was the case in Poland during the flood in 2010. One of the main threats to the safety of the embankment is the development of filtration and erosion processes both in its body and the ground. The existing practice of monitoring and assessing the condition of flood embankments is insufficient to ensure the safety of these facilities. They are based primarily on local inspection and the implementation of geotechnical research in cross-sections spaced from each other. The basic disadvantage of traditional methods is their point (local) character. Identification of filtration and erosion processes, especially in their initial phase of development and assessment of their kinetics with these methods is usually impossible. Designing shafts due to their location, shape and material is quite complicated [19,20]. Monitoring of flood protections requires methods and systems which will have the following features: monitoring of destructive processes in real time during floods, continuous monitoring of space in the space, monitoring of early and precise detection of the destructive process, the possibility of evaluating the kinetics of the destructive process, the possibility of developing an automatic alarm system informing about the occurrence of a destructive process, a damage-resistant installation operating without a maintenance service. Data acquisition In systems based on the electrical tomography (ET) method, the data acquisition system collects measurements of the voltages generated by the electrodes [1-5,7-9, 17, 17- 25]. These types of data can be processed locally or can reach the central analytical system. It mainly depends on such factors as: the geospatial dimensions of the monitored object, the computational power of the ET device, as well as the required resolution of the reconstructed image. Traditional data collection and pro[...]

Area monitoring using the ERT method with multisensor electrodes DOI:10.15199/48.2019.01.39

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Tomography is a technique that allows obtaining a cross-sectional image of the examined object on the basis of data from the measurement of a given physical value (radiation, capacity, resistance, etc.) at selected points usually lying on the edge of the tested area. The resulting measurement vector is used to reconstruct the crosssection image using appropriate algorithms. The obtained image represents the distribution of a certain feature of the examined object depending on the type of tomography used. It can be material density, concentration, electrical permittivity, conductivity, etc. Electrical tomography covers many tomographic imaging methods based on the processing of various electrical parameters [1,3,4,7,9,10,12-14]. Despite the fact that many methods have already been developed for assessing damage to flood embankments, there is no single universal tool for their diagnosis and monitoring. In this paper, a new method for testing flood embankments and landfills by means of electrical resistive tomography (ERT) was presented. For the needs of the research, a special measuring system was developed with special multisensor electrodes for depth measurements using ERT. The algorithms used for image reconstruction were based on gradient and topological methods. After minor modifications, it is possible to apply the discussed technique to solving reverse problems in electrical tomography [6, 18-23]. The combination of tomographic techniques with reconstruction algorithms allowed non-invasive and more accurate spatial assessment of seepages and damages to flood protections. Model Electric tomography including ERT enables non-invasive measurements of various types of technical objects. The i[...]

Industrial processes control with the use of a neural tomographic algorithm DOI:10.15199/48.2019.02.22

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Process tomography is picking up in significance alongside innovative advancement [1], [2]. At present, a significant trend can be watched for the robotization of modern procedures, which is firmly identified with process control. The need to automate the control of innovative procedures is one of the fundamental purposes behind the dynamic improvement of IT information handling strategies [3], [4]. Simulation and experimental tests are an important condition for optimizing the control of processes carried out by liquid and suspension mixing systems that under certain circumstances can crystallize [5]. An example of such a substance is biodiesel. Common measurement tools used to quantify physicochemical processes, such as sensors and markers, are often characterized by evaluation capabilities limited to specific points. Due to the high degree of difficulty in modeling the mixing and heating processes of crystallizing substances [6], which are characterized by a distinct non- Newtonian flow, traditional Computational Fluid Dynamics models do not provide a suitable basis for dimensioning mixing and heating systems, and therefore become useless. Classical models do not take into account granulometric parameters. The method of determining the rheological properties of liquids is difficult. In addition, traditional models used to simulate the mixing and heating of multiphase systems are still inaccurate [7], [8]. This fact may lead to misinterpretations, especially with regard to modeling and simulation of mixing and heating processes of non-Newtonian liquids, viscous and loaded with foreign particles. For this reason, reliable forecasts regarding the course of such processes are virtually impossible. The above-mentioned problems are an important reason to intensify efforts to develop an effective method of monitoring and supervising liquid crystallization processes [9]. Electrical impedance tomography (EIT) is a modality with[...]

Detection of seepages in flood embankments using the ElasticNET method DOI:10.15199/48.2019.01.40

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Electric tomography is based on the transformation of data taken from the surface of the tested object into the image of its cross-section. There are many methods to optimize the obtained image by solving the appropriate objective function [1-5,13,15,16,20-25,32]. The algorithm based on the ElasticNET presented in this article is a new proposal in tomography. Fig. 1. Model of measuremnt system. The way of working of electrical impedance tomography (EIT) consists in introducing electrical voltage to the tested object by means of a set of electrodes located on the surface of the object. Next, the measured values of electrical potentials between individual electrode pairs are collected. Conductance of individual sections of the crosssection of the tested object is reconstructed on the basis of known values of voltages and measured values of potentials. Reconstruction of the image obtained by electrical tomography requires sophisticated modeling. This method of imaging consists in the fact that the conductivity distribution of the tested object is estimated on the basis of measurements of electrical voltages and electrode potentials on the surface of their contact with the tested object. In order to obtain quantitative data on changes in the conductivity inside an object, it is more effective to apply a non-linear model in differential imaging [1,6-12,14,17- 199,26-31]. In Fig. 1 shows the model of the measurement system. ElasticNET Let’s consider the problem of recognizing linear dependencies (1) Y  X   where Y Rn , X Rnk1 are the observation matrices of a output variable and predictive variables respectively,   Rk1means a matrix of structural parameters, while  Rn vector of independent random variables. The wellknown method of least squares consists in estimating unknown parameters &[...]

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