The paper presents the experience of using the ŁPrP, ŁPKO, ŁPSp, ŁPSpA i ŁPSp3R types of flattened supports for longwall entries in the conditions of the JSW S.A. Knurów-Szczygłowice coal mine. The article concentrates on the support solutions applied in the conditions of the mine and the results in terms of stability and usefulness of the structures of the supports. An analysis of the load bearing capacity and technological conditions has been conducted for various flattened supports solutions, with special consideration given to the ŁPSp and ŁPrPJ support sets. Comparing these two, the ŁPSp exhibits a load bearing capacity that is 21% higher while using 31% less steel mass. The experiment results allowed to determine that the ŁPSpA and ŁPSp3R support types are an advantageous solutions in case of longwall set-up rooms.
Steel arch-rectangular support has a wide range of applications in Polish coal mines due to its asymmetrical shape. The frame has an arched outline on one side of the side wall, while on the opposite side it is rectangular. As a result, the support is ideal for securing set up room and recovery room. It can also be successfully used to secure three-way intersections of underground workings. To a large extent, however, the importance of these advantages is diminished by relatively low load-bearing parameters, resulting from a partially straight canopy, as well as the asymmetrical distribution of the load acting on the support in underground conditions. In order to ensure the proper and optimal operation of such frames, in addition to the standard requirements for roof supports, additional conditions must be met. The basic requirement is to support the end of the canopy on the corner of the excavation. This article presents examples of arch-rectangular supports, their applications as well as laboratory tests and strength analysis of the frames and its elements. These tests allowed the requirements regarding the construction of the frame, the selection of the support and the conditions of building in the excavation to be specified.
The problems related to construction production are multi-faceted and complex. This has promoted the search for different methods/approaches for analizing the data which supports the decision-making process in the construction industry. In the article the authors focus their attention on well-known methods and tools, and on some new approaches to solving decision-making problems. The aim of the article is to analyze the methods used to analyse data in a construction company, convey their advantages and disadvantages, and specify the degree of efficiency in the discussed area.
Having increasingly tightened geological and mining conditions in which the extraction of copper ore deposits in Poland is conducted, ensuring effective and safe mining is presently becoming a key task and a significant challenge for mine operators, mainly in the field of ground support systems being the equivalent for the new geological/mining conditions. As one may expect, these conditions shall be characterized by higher values of the primary stress tensor elements as well as the lower deformability and higher strength of the rock mass surrounding the copper ore body. T his means that in the near future, the rock bursts problem will become one of the most important issues deciding on the economy and safety within the newly developed mining areas. T herefore developing a novel effective ductile ground support systems which could be able to control the rock mass movement in squeezing and burst-prone rock conditions is recommended. T his type of requirement may fulfil only ductile or, in other words, the kinetic energy-absorbing systems, which permit slowing down a movement of violently ejected rock blocks. T his paper’s objective is to present the idea of the development of a new type of an effective and low cost ductile resin anchored rockbolt system with smooth and of the square cross-section steel rod is formed in coil shape of different pitch. T he developed bolt prototypes have been tested underground in the G-11 section of the Rudna mine. Results of the pull-out tests, involving different bolts’ shapes and different sliding materials set on the rockbolts’ rods, have proved those bolts’ efficiency as an element of the ductile support system.
The paper presents the statical research tests of rod bolt made of plastic with a length of 5.5 m, which were performed in a modern laboratory test facility at the Department of Underground Mining of the University of Science and Technology. Innovative The Self-excited Acoustic System (SAS) used to measure stress changes in the bolt support was characterized. The system can be used for the non-destructive evaluation of the strain of the bolt around the excavations as well as in tunnels. The aim of the study was to compare the re-sults recorded by two different measuring systems, thanks to which it will be possible to assess the load of long bolt support by means of the non-destructive method. The speed and simplicity of measurement, access to the sensors, accuracy of measurement and reading should be kept in mind in determining the load of rock bolt support . In addition, the possibility of damage to the sensor as a re-sult of technological or natural hazards should also be taken into account. In economic conditions, the „technical - balance laws of production”, which ex-cludes the use of load sensors on each bolt must be preserved. The use of indi-vidual load sensors of rock bolt support for the boundary state, allows appro-priate protection actions of the mining crew against sudden loss of excavation stability to be taken. The paper presents two basic effects used in the ultrasonic measurement sys-tem. The first result was the existence of stable limit cycle oscillations for posi-tive feedback. This effect is called the self-excited effect. The second effect is called the elasto-acoustic effect. It means that with the change of elastic stress-es in the material bring the change of the speed of propagation of the wave. In this connection, the propagation time between measuring heads is also changed. This effect manifests itself in the change in the oscillation frequency of the self-excited system. For this reason, by measuring the frequency of self-excited oscillation, it is possible to indirectly determine the level of effort of the tested material.
The article describes Family Group Conference method, which was initiated in Poland over 10 years ago by J. Przepierski. The method is presented in historical context of their theoretical foundations and particular practical assets justifying its application in work with families in a crisis situation and moments of difficulties, which might constitute an obstacle in the use of the method.
Coal mining is one of the most important sectors of the Polish industry. It can be said that the coal is a national raw material. This results in Poland being a pioneer in the European Union in terms of coal mining as well as its use in the production of electricity and heat. There are many companies in Poland which have been established and developed around the coal mining industry aimed at coal extracting. The operations of those companies depends on the condition of the mining companies and their cooperation with them: commercial, service and advisory, called referred to as “mining supporting companies”. The article focuses on the results of a survey carried out in mining supporting companies, such as mining machinery and equipment manufacturers, mining-related service companies and mining-related research and development institutions. The authors evaluated the relationship and dependence of those companies on the mining industry. It was assumed that the measure of the mining supporting companies condition is the overall quantity of public related payments contributed to the state budget and local budgets. In the article, the authors raised the problem of the size of losses for public finances, as a result of the significant limitations of financial flows from the mining companies. The surveyed companies are those associated with the Polish Mining Chamber of Industry and Commerce. As a result, the authors prepared conclusions regarding the dependence of the mining supporting companies on the situation of the mining subsector.
Caving in the excavation of mining galleries is a dangerous phenomenon, resulting in a threat to the health and life of humans, technological difficulties (transport, ventilation, etc.) and economic losses. Mining galleries list: design errors, runtime errors, errors and random causes among the causes of the caving occurring in recent periods in the excavation of underground coal mines. Examples in the recent period of caving in the excavation of mining galleries in coal mines indicated that one of the main causes of the situation was the loss of capacity and double timber technical wear caused by the corrosion of the profile. In practice, the caving that occur as a result of the technical wear can be divided into the breaking arc of a roof – bar, the loss of stability of one of the heading walls and a total heading collapse. On the basis of the carried out analysis of these cases, guidelines were proposed for improving the safe operation of the workings. The improvement of support stability may be achieved by applying additional supports, stabilizing the structure by bolting the support sets or by introducing a fiber-reinforced concrete coating with injection into the rock mass. Examples of caving occurring in the excavation, for which the preparatory selection of support does not match the geological-mining conditions, were also presented. The summary indicated the importance of diagnostics roadway in the safe and efficient conduct of mining that should be covered by the operational rules, and their scope and frequency should be adapted to the rank of the occurrence of hazard and support construction.
Using renewable energy sources for electricity production is based on the processing of primary energy occurring in the form of sun, wind etc., into electrical energy. Economic viability using those sources in small power plants strongly depends on the support system, based mainly on financial instruments. Micro-installations, by using special instruments dedicated to the prosumer market may become more and more interesting not only in terms of environmental energy, but also financial independence. In the paper, the term hybrid power plant is understood to mean a production unit generating electricity or electricity and heat in the process of energy production, in which two or more renewable energy sources or energy sources other than renewable sources are used. The combination of the two energy sources is to their mutual complementarity, to ensure the continuity of the electricity supply. The ideal situation would be if both sources of energy included in the hybrid power plant continuously covered the total demand for energy consumers. Unfortunately, due to the short-term and long-term variability of weather conditions, such a balance is unattainable. The paper assesses the possibility of balancing the hybrid power plant in daily and monthly periods. Basic types of power plants and hybrid components and system support micro-installations were characterized. The support system is based particularly on a system of feed-in tariffs and the possibility of obtaining a preferential loan with a subsidy (redemption of part of the loan size). Then, an analysis of energy and economic efficiency for a standard set of hybrid micro-installations consisting of a wind turbine and photovoltaic panels with a total power of 5 kW, were presented. Fourteen variants of financing, economic efficiency compared with the use of the method of the simple payback period were assumed.
Assumptions of the major political and legal documents of the European Union, dedicated to energy efficiency and energy performance of buildings provide the Member States with relevant instruments supporting improvement of the ambient air qualityby dissemination of measures reducing energy demand and promotion of renewable energysources. Mainstreaming EU legislation into national regulations constitutes initial stage of the long term process of supporting implementation of energy efficiency measures. Experience in the improvement of energy performance of the residential buildings revealslimited efficiency of the measures implemented up to date, which results in significantair pollution of Polish cities. The national Action Plans had adopted a limited scope of recommendations included in the EU directives, hence the process meets significant challenges.The article describes adaptation of the relevant EU directives as well as the National Urban Policy in terms of the potential to effectively address faced challenges.
The aim of this study is to present an exemplary cartographic visualization of fi re hydrants data consisting of a set of thematic maps containing various information related to the location of hydrants, buildings and driveways in geographic space, and relationships existing between them. Identification of these relationships requires spatial analysis, and illustrating them requires the use of appropriate cartographic presentation methods. The study was conducted on a part of the city of Poznan using data on hydrants’ location and type collected and provided by the Fire Department. Geometric data, obtained using geoprocessing algorithms, were assigned appropriate symbols, which lets differentiate them qualitatively and quantitatively. An emphasis is placed on the use of adequate visual variables and on the cartographic communication efficiency. The result of the study is a cartographic visualization in the form of series of thematic maps arranged in a logical sequence, and providing information about the secured area. The thematic layers presenting the same area were arranged in different arrangements with maintenance of the reference layers, ensuring the ease of correlation. Such a cartographic visualization provides knowledge about the spatial distribution and diversity of objects and the relationships between them. It may be an important source of knowledge both at the identification stage and at the operational stage when conducting a fire fighting action.
Power electronic circuits (PECs) are prone to various failures, whose classification is of paramount importance. This paper presents a data-driven based fault diagnosis technique, which employs a support vector data description (SVDD) method to perform fault classification of PECs. In the presented method, fault signals (e.g. currents, voltages, etc.) are collected from accessible nodes of circuits, and then signal processing techniques (e.g. Fourier analysis, wavelet transform, etc.) are adopted to extract feature samples, which are subsequently used to perform offline machine learning. Finally, the SVDD classifier is used to implement fault classification task. However, in some cases, the conventional SVDD cannot achieve good classification performance, because this classifier may generate some so-called refusal areas (RAs), and in our design these RAs are resolved with the one-against-one support vector machine (SVM) classifier. The obtained experiment results from simulated and actual circuits demonstrate that the improved SVDD has a classification performance close to the conventional one-against-one SVM, and can be applied to fault classification of PECs in practice.
Entries in steeply pitching seams have a more complex stress environment than those in flat seams. This study targets techniques for maintaining the surrounding rock mass stability of entries in steep seams through a case study of a steep-seam entry at a mine in southern China. An in-depth study of the deformation and instability mechanisms of the entry is conducted, employing field measurement, physical simulation experiment, numerical simulation, and theoretical analysis. The study results show that the surrounding rock mass of the entry is characterised by asymmetrical stress distribution, deformation, and failure. Specifically, 1) the entry deformation is characterised by a pattern of floor heaving and roof subsidence; 2) broken rock zones in the two entry walls are larger than those in the roof and floor, and the broken rock zone in the seam-floor side wall is larger than that in the seam-roof side wall; 3) rock bolts in the middle-bottom part of the seam-floor side wall of the entry are prone to failure due to tensile stress; and 4) rock bolts in the seam-roof side wall experience relatively even load and relatively small tensile stress. Through analysis, disturbances were found to occur in both temporal and spatial dimensions. Specifically, in the initial mining stage, the asymmetrical rock structure and stress distribution cause entry deformation and instability; during multiple-seam multiple-panel mining operations, a wedge-shaped rock mass and a quasi-arc cut rock stratum formed in the mining space may cause subsidence in the seam-floor side wall of the entry and inter-stratum transpression, deformation, and instability of the entry roof and floor. The principles for controlling the stability of the surrounding rock mass of the entry are proposed. In addition, an improved asymmetrical coupled support structure design for the entry is proposed to demonstrate the effective control of entry deformation.
The article herein presents the method and algorithms for forming the feature space for the base of intellectualized system knowledge for the support system in the cyber threats and anomalies tasks. The system being elaborated might be used both autonomously by cyber threat services analysts and jointly with information protection complex systems. It is shown, that advised algorithms allow supplementing dynamically the knowledge base upon appearing the new threats, which permits to cut the time of their recognition and analysis, in particular, for cases of hard-to-explain features and reduce the false responses in threat recognizing systems, anomalies and attacks at informatization objects. It is stated herein, that collectively with the outcomes of previous authors investigations, the offered algorithms of forming the feature space for identifying cyber threats within decisions making support system are more effective. It is reached at the expense of the fact, that, comparing to existing decisions, the described decisions in the article, allow separate considering the task of threat recognition in the frame of the known classes, and if necessary supplementing feature space for the new threat types. It is demonstrated, that new threats features often initially are not identified within the frame of existing base of threat classes knowledge in the decision support system. As well the methods and advised algorithms allow fulfilling the time-efficient cyber threats classification for a definite informatization object.
The article presents the results of tests on SHC-40 hydraulic props equipped with two types of valve blocks: standard (with spring steel cylinder) and BZG-2FS (with gas spring). The research was conducted using impact mass of 4,000 kg and with extreme dynamic load of free fall impact mass of 20,000 kg released from different heights h. The dynamic tests involved a camera with the speed of image capture up to 1,200 frames/sec, which made it possible to register the stream of liquid at the dynamic load and to determine the valve opening time. The study conducted on SHC-40 NHR10 props equipped with two types of valve blocks: a standard and the BZG-2FS fast acting relief, showed that the prop with the BZG-2FS block is more suitable and more effective in the case of areas with high risk of mining tremors and rapid stress relief of a seam. Research methodology developed in the Central Mining Institute combines digital recording technique of pressure in a prop and fast registration of the images, and allows to acquire more accurate analysis of dynamic phenomena in the prop during testing.
This paper presents the design process and the results of a novel fall detector designed and constructed at the Faculty of Electronics, Military University of Technology. High sensitivity and low false alarm rates were achieved by using four independent sensors of varying physical quantities and sophisticated methods of signal processing and data mining. The manuscript discusses the study background, hardware development, alternative algorithms used for the sensor data processing and fusion for identification of the most efficient solution and the final results from testing the Android application on smartphone. The test was performed in four 6-h sessions (two sessions with female participants at the age of 28 years, one session with male participants aged 28 years and one involving a man at the age of 49 years) and showed correct detection of all 40 simulated falls with only three false alarms. Our results confirmed the sensitivity of the proposed algorithm to be 100% with a nominal false alarm rate (one false alarm per 8 h).
This paper proposes a soft sensing method of least squares support vector machine (LS-SVM) using temperature time series for gas flow measurements. A heater unit has been installed on the external wall of a pipeline to generate heat pulses. Dynamic temperature signals have been collected upstream of the heater unit. The temperature time series are the main secondary variables of soft sensing technique for estimating the flow rate. A LS-SVM model is proposed to construct a non-linear relation between the flow rate and temperature time series. To select its inputs, parameters of the measurement system are divided into three categories: blind, invalid and secondary variables. Then the kernel function parameters are optimized to improve estimation accuracy. The experiments have been conducted both in the single-pulse and multiple-pulse heating modes. The results show that estimations are acceptable.
In the paper an approach to decision making in situations with non-point-like characterisation and subjective evaluation of the actions is considered. The decision situation is represented mathematically as fuzzy multiobjective linear programming (fMOLP) model, where we apply the reduced fuzzy matrices instead of fuzzy classical numbers. The fMOLP model with reduced parameters is decomposable into the set of point-like models and the point-like models enable effective construction of an optimisation procedure – fBIP, see Wojewnik (2006ab), extending the bireference procedure by Michalowski and Szapiro (1992). The approach is applied to a fuzzy optimization problem in the area of telecommunication services.
A significant part of the knowledge used in the production processes is represented with natural language. Yet, the use of that knowledge in computer-assisted decision-making requires the application of appropriate formal and development tools. An interesting possibility is created by the use of an ontology that is understandable both for humans and for the computer. This paper presents a proposal for structuring the information about the foundry processes, based on the definition of ontology adapted to the physical structure of the ongoing technological operations that make up the process of producing castings.
As experience shows the practical, reliable assessment and optimisation of total costs of logistical processes implemented in supply chains of foundry plants is a quite complex and complicated process, because it requires to enclose all, without exception, performed actions, including them in various reference cross-sections, systematic activities and finally transforming them in a totally homogenous collection. Only solid analysis and assessment of assortment management in logistical supply systems in foundry plants of particular assortment groups allows to lower the supply costs significantly. In the article the analysis and assessment of the newest implemented optimising algorithms are presented in the process stock management of selected material groups used in a production process of a chosen foundry plant. A practical solution to solve a problem of rotary stock cost minimisation is given as well as of costs while creating a stock with the usage of economical volume and value of order.
Affective computing studies and develops systems capable of detecting humans affects. The search for universal well-performing features for speech-based emotion recognition is ongoing. In this paper, a small set of features with support vector machines as the classifier is evaluated on Surrey Audio-Visual Expressed Emotion database, Berlin Database of Emotional Speech, Polish Emotional Speech database and Serbian emotional speech database. It is shown that a set of 87 features can offer results on-par with state-of-the-art, yielding 80.21, 88.6, 75.42 and 93.41% average emotion recognition rate, respectively. In addition, an experiment is conducted to explore the significance of gender in emotion recognition using random forests. Two models, trained on the first and second database, respectively, and four speakers were used to determine the effects. It is seen that the feature set used in this work performs well for both male and female speakers, yielding approximately 27% average emotion recognition in both models. In addition, the emotions for female speakers were recognized 18% of the time in the first model and 29% in the second. A similar effect is seen with male speakers: the first model yields 36%, the second 28% a verage emotion recognition rate. This illustrates the relationship between the constitution of training data and emotion recognition accuracy.
Accurate network fault diagnosis in smart substations is key to strengthening grid security. To solve fault classification problems and enhance classification accuracy, we propose a hybrid optimization algorithm consisting of three parts: anti-noise processing (ANP), an improved separation interval method (ISIM), and a genetic algorithm-particle swarm optimization (GA-PSO) method. ANP cleans out the outliers and noise in the dataset. ISIM uses a support vector machine (SVM) architecture to optimize SVM kernel parameters. Finally, we propose the GA-PSO algorithm, which combines the advantages of both genetic and particle swarm optimization algorithms to optimize the penalty parameter. The experimental results show that our proposed hybrid optimization algorithm enhances the classification accuracy of smart substation network faults and shows stronger performance compared with existing methods.
The model is developed for the intellectualized decision-making support system on financing of cyber security means of transport cloud-based computing infrastructures, given the limited financial resources. The model is based on the use of the theory of multistep games tools. The decision, which gives specialists a chance to effectively assess risks in the financing processes of cyber security means, is found. The model differs from the existing approaches in the decision of bilinear multistep quality games with several terminal surfaces. The decision of bilinear multistep quality games with dependent movements is found. On the basis of the decision for a one-step game, founded by application of the domination method and developed for infinite antagonistic games, the conclusion about risks for players is drawn. The results of a simulation experiment within program implementation of the intellectualized decision-making support system in the field of financing of cyber security means of cloudbased computing infrastructures on transport are described. Confirmed during the simulation experiment, the decision assumes accounting a financial component of cyber defense strategy at any ratios of the parameters, describing financing process.
In this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones – the healthy blood cells (erythrocytes) and the pathologic ones (echinocytes). The separated blood cells are analysed in terms of their most important features by the eigenfaces method. The features are the basis for designing the neural network classifier, learned to distinguish between erythrocytes and echinocytes. As the result, the proposed system is able to analyse the smear blood images in a fully automatic way and to deliver information on the number and statistics of the red blood cells, both healthy and pathologic. The system was examined in two case studies, involving the canine and human blood, and then consulted with the experienced medicine specialists. The accuracy of classification of red blood cells into erythrocytes and echinocytes reaches 96%.