The analysis of available literature indicates that tests of products sound quality, which would not involve participation of groups of listeners supposed to evaluate the sounds emitted by these products, are neither carried out in Poland, nor in the world. That results in the fact that the products sound quality is determined on the basis of psychoacoustic information and comprises both objective and subjective factors of sound perception. With reference to those factors and to different life cycles of the machine, an original definition of the “sound quality of the machine” has been developed and presented in this article. The global index of the acoustic quality of the machine, accounting for the relations between the noise level at the workstation and the selected parameters characterising both the machine's sound activity and the working environment, was adopted as the measure of the sound quality of the machine. The experiments that followed confirmed the appropriateness of the assessment made with the use of the global index of acoustic quality.
Development of mineral deposits located at significant depth may be carried out by means of vertical shafts. Shaft sinking technology usually requires a number of works to be carried out, including the selection of appropriate excavating techniques adapted to geological and hydrological conditions, including natural hazards. The production technology and the machines used determine the level of sinking costs and execution period. The article discusses the excavating technologies currently used across the world. Then the assumptions, concept and construction of a new generation of shaft sinking system were presented. The proposed new solution of the system and the excavating technology allow for parallel execution of key processes related to winning, loading, transport and shaft wall-side lining, which significantly increases the progress of sinking. The shaft sinking system was created by scientists from AGH in cooperation with KOPEX – Przedsiębiorstwo Budowy Szybów S. A. and Instytut Techniki Górniczej KOMAG.
The present paper aims at presenting a short study of the prefixed forms of the Polish verb pić (‘to drink’) (napić, wypić, popić, przepić, opić, zapić, etc.) and their French equivalents found in two parallel corpora: Glosbe and Reverso Context. In the first part, selected theoretical approaches concerning the verbal prefixation in Polish are discussed, with particular attention to the hypothesis of “perfective hypercategory” by Włodarczyk and Włodarczyk (2001b). The second part focuses on the results of the contrastive Polish-French analysis. The research is carried out in the general framework of the Aktionsarten theory and tries to discover by which linguistic means (grammatical and/or lexical) the French language expresses different semantic values conveyed by the Polish prefixes. The results of the analysis are appropriately formalized according to the principles of the object-oriented approach by Banyś (2002a, b), i.e. described by the syntactic-semantic schemes (which, after several changes of specifi cation, can be applied in the machine translation programs). The purpose of the investigation is, therefore, twofold: theoretical, since it is the matter of discovering certain relations between two languages expressing differently a given linguistic phenomenon, and practice, which consists in formulating interlinguistic correspondence rules for the purpose of the Polish-French translation.
The article presents the results of research on the finishing of M63 Z4 brass by vibratory machining. Brass alloy was used for the research due to the common use of ammunition elements, cartridge case and good cold forming properties on the construction. Until now, the authors have not met with the results of research to determine the impact of abrasive pastes in container processing. It was found that the additive for container abrasive treatment of abrasive paste causes larger mass losses and faster surface smoothing effects. The treatment was carried out in two stages: in the first stage, the workpieces were deburred and then polished. Considerations were given to the impact of mass of workpieces, machining time and its type on mass loss and changes in the geometric structure of the surface. The surface roughness of machining samples was measured with the Talysurf CCI Lite optical profiler. The suggestions for future research may be to carry out tests using abrasive pastes with a larger granulation of abrasive grains, and to carry out tests for longer processing times and to determine the time after which the parameters of SGP change is unnoticeable.
New materials require the use of advanced technology in manufacturing parts of complex shape. One of the modern non-conventional technology of manufacturing difficult to cut materials is the wire electrical discharge machining (WEDM). The article presents the results of theoretical and experimental research in the influence of the WEDM conditions and parameters on the shape deviation during a rough cut. A numerical model of the dielectric flow in the gap (ANSYS) was developed. The influence of the dielectric velocity field in the gap on the debris evacuation and stability of WEDM process was discussed. Furthermore, response surface methodology (RSM) was used to build empirical models for influence of the wire speed Vd, wire tension force Fn, the volume flow rate of the dielectric Qv on the flatness deviation after the WEDM.
Asynchronized (doubly-fed) machines with two (three) excitating winding and reversing excitation system allow to control vector of magnetomotive force. This solution allows separating regulation of the electromagnetic torque (active power) and voltage (reactive power). This paper describes the experience in the development and operation of asynchronized turbogenerators and condensers.
Traffic classification is an important tool for network management. It reveals the source of observed network traffic and has many potential applications e.g. in Quality of Service, network security and traffic visualization. In the last decade, traffic classification evolved quickly due to the raise of peer-to-peer traffic. Nowadays, researchers still find new methods in order to withstand the rapid changes of the Internet. In this paper, we review 13 publications on traffic classification and related topics that were published during 2009-2012. We show diversity in recent algorithms and we highlight possible directions for the future research on traffic classification: relevance of multi-level classification, importance of experimental validation, and the need for common traffic datasets.
The study aimed to apply the protection from damage to engineering facilities located near a planned underwater aggregate extraction. The analysis was conducted in compliance with mining regulations and expert opinions. The study also aimed to assess the precision and correctness of the extraction, due to economic aspects. To reach the goals, in-situ research of the mining area was conducted, with the help of an advanced bathymetric device, based on the USV methodology. The instrument – named by the author as Smart-Sonar-Boat – was especially designed for underwater surveys in open-pit aggregate mines. The study analyzed the “Dwory” open-pit mine, located in southern Poland in the city of Oświęcim. The bathymetric results obtained contributed to improving the observation of changes in the bottom during the extraction. The applied USV method allowed for conducting the reliable evaluation of the mining work.
Quality evaluation is very important for haptic rendering. In this paper, an objective evaluation method for a haptic rendering system based on haptic perception features is proposed. In the method, the haptic rendering process is compared to the real world perception process in a simple standardized procedure based on feature extraction and data analysis. A complete evaluation process for a simple haptic rendering task of pressing a virtual spring is presented as an example to explain the method in detail. Compared with the traditional objective method based on error statistics, the method is more concerned about the consistency of human subjective feelings rather than physical parameters, which makes the evaluation process more consistent with the haptic perception mechanism. The results of comparative analysis show that the method presented in this paper is simple, gives reliable results reflecting the consistency with subjective feeling and has a better discrimination ability for different kinds of devices and algorithms compared with the traditional evaluation methods.
To avoid of manipulating search engines results by web spam, anti spam system use machine learning techniques to detect spam. However, if the learning set for the system is out of date the quality of classification falls rapidly. We present the web spam recognition system that periodically refreshes the learning set to create an adequate classifier. A new classifier is trained exclusively on data collected during the last period. We have proved that such strategy is better than an incrementation of the learning set. The system solves the starting–up issues of lacks in learning set by minimisation of learning examples and utilization of external data sets. The system was tested on real data from the spam traps and common known web services: Quora, Reddit, and Stack Overflow. The test performed among ten months shows stability of the system and improvement of the results up to 60 percent at the end of the examined period.
The paper consists the problem of developing a scientific toolkit allowing to predict the thermal state of the ingot during its formation in all elements of the casting and rolling complex, between the crystallizer of the continuous casting machine and exit from the furnace. As the toolkit for the decision making task the predictive mathematical model of the ingot temperature field is proposed. Displacement between the various elements of the CRC is accounted for by changing the boundary conditions. Mass-average enthalpy is proposed as a characteristic of ingot cross-section temperature state. The next methods of solving a number of important problems with the use of medium mass enthalpy are developed: determination of the necessary heat capacity of ingots after the continuous casting machine for direct rolling without heating; determination of the rational time of alignment of the temperature field of ingots having sufficient heat capacity for rolling after casting; determination of the total amount of heat (heat capacity) required to supply the metal for heating ingots that have insufficient amount of internal heat.
This paper presents a study of control strategies for 5-phase permanent magnet synchronous motors (PMSMs) supplied by a five-leg voltage source inverter. Based on the vectorial decomposition of the multi-phase machine, fictitious machines, magnetically decoupled, allow a more adequate control. In this paper, our study focuses on the vector control of a multi-phase machine using a linear proportional-integral-derivative (PID) current regulator in the cases of sinusoidal and trapezoidal back-electromotive force (EMF) waveforms. In order to determine currents’ references, two strategies are adopted. First one aims to minimize copper losses under constant torque, while the second one targets to increase torque for a given copper losses. These techniques are tested under a variable speed control strategy based on a proportional-integral (PI) regulator and experimentally validated.
The NOMAD project was a survey to examine the noise-related content of instructions supplied with machinery offered for purchase in Europe. The project collected more than 1 500 instructions from machines covering 40 broad machine-families and from 800 different manufacturing companies. These instructions were analyzed to determine compliance with the requirements of the Machinery Directive, and assess the quality of information. The general state of compliance of machinery instructions with the noise-related requirements of the Machinery Directive was found to be very poor: 80% of instructions did not meet legal requirements. Some required numerical values relating to noise emissions were often missing. Where values were given, they were often not traceable to machine operating conditions or measurement methods, and not credible either against stated conditions/methods or as warnings of likely risk in real use. As a consequence, it is considered highly likely that, in making a machinery procurement decision, employers are prevented from taking noise emissions into account, and understanding what is necessary to manage the risks from noise relating to equipment that is procured. Recommendations are made for actions aimed at bringing about a global improvement to the current situation. Targeted actions are now proposed by “ADCO Machinery Group” aimed at raising awareness of the legal requirements, responsibilities and actions required among the various groups who have parts to play in the system - machine manufacturers, machine users, occupational safety and health professionals, and standards-makers. Recommendations are also made aimed at providing, or improving, tools and resources for all these actors.
The aim of the study was to identify acoustic and structural modes in the spectrum obtained exper-imentally inside an operator's cab in a bulldozer. Measurements were taken inside the operator's cab in a caterpillar-track bulldozer Polremaco TD12NPH2E-2000, designed for work in underground mine enclosures. The acoustic pressure spectrum was obtained for varied rotational speeds of the engine during the free run of the machine. The reverberation time of the cab was determined basing on the pulse-type excited pressure response, followed by identification of the spectral components registered by measurements. Thus, identified frequencies were compared with natural acoustic frequencies registered inside the operator's cab and with frequencies associated with the valves and ignition frequencies due to rotational speed and natural frequencies of structural vibrations of the cab's walls. This study was conducted in an attempt to reduce the noise inside the operator's cab using passive methods
The study presented here offers an analysis of the heat flow through the wall of the Yankee cylinder when regarded as a thin-walled vessel. The effect of the selected design and process parameters (i.e. cylinder diameter and steam pressure) on density of the heating stream has been analyzed and discussed for both cast iron and steel cylinders. Based on the work presented here, the optimal ranges for steam pressure have been derived and proposed for cylinders mounted at various locations within the drying section.
Lately, there has been increased interest in hybrid excitation electrical machines. Hybrid excitation is a construction that combines permanent magnet excitation with wound field excitation. Within the general classification, these machines can be classified as modified synchronous machines or inductor machines. These machines may be applied as motors and generators. The complexity of electromagnetic phenomena which occur as a result of coupling of magnetic fluxes of separate excitation systems with perpendicular magnetic axis is a motivation to formulate various mathematical models of these machines. The presented paper discusses the construction of a unipolar hybrid excitation synchronous machine. The magnetic equivalent circuit model including nonlinear magnetization curves is presented. Based on this model, it is possible to determine the multi-parameter relationships between the induced voltage and magnetomotive force in the excitation winding. Particular attention has been paid to the analysis of the impact of additional stator and rotor yokes on above relationship. Induced voltage determines the remaining operating parameters of the machine, both in the motor and generator mode of operation. The analysis of chosen correlations results in an identification of the effective control range of electromotive force of the machine.
The paper presents a concept, a construction, a circuit model and experimental results of the double-rotor induction motor. This type of a motor is to be implemented in the concept of the electromagnetic differential. At the same time it should fulfill the function of differential mechanism and the vehicle drive. One of the motor shafts is coupled to the direction changing mechanical transmission. The windings of the external rotor are powered by slip rings and brushes. The inner rotor has the squirrel-cage windings. The circuit model parameters were calculated based on the 7.5 kW real single-rotor induction motor (2p = 4). Experimental verification of the model was based on comparison between the mentioned single-rotor motor and double-rotor model with the outer rotor blocked. The presented results showed relatively good compliance between the model and real motor.
An early fault diagnostic method of Direct Current motors was presented in this article. The proposed method used acoustic signals of a motor. A method of feature extraction called MSAF-RATIO30-EXPANDED (method of selection of amplitudes of frequencies – ratio 30% of maximum of amplitude – expanded) was presented and implemented. An analysis of proposed method was carried out for early fault states of a real DC motor. Four following states of the DC motor were measured and analyzed: the healthy DC motor, DC motor with 3 shorted rotor coils, DC motor with 6 shorted rotor coils, DC motor with a broken coil. Measured states were caused by natural degradation of the DC motor. The obtained results of analysis were good. The presented early fault diagnostic method can be used for protection of DC motors.
The condition monitoring techniques like acoustic emission, vibration analysis, and infrared thermography, used for the failure diagnosis of bearings, require longer processing time, as they have to perform acoustical measurement followed by signal processing and further analysis using special software. However, for any bearing, its period of usage can be easily determined within an hour, by measuring the bearing sound, using sound level meter (SLM). In this paper the acoustical analysis of the spindle bearing of a radial drilling machine was performed using SLM, by measuring the sound pressure level of the bearing in decibels, for different frequencies, while muting all the other noises. Then using an experimental set up, two database readings were taken, one for new bearing and the other for completely damaged bearing, both are SKF6207, which itself is the spindle bearing. From these three sets of sound pressure level readings, the period of usage of the spindle bearing, was calculated using an interpolation equation, by substituting the life of the bearing from the manufacturer’s catalogue. Therefore, for any machine with a SKF6207 bearing, its usage time can be estimated using the database readings and one measurement on that machine, all with the same speed.
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.
In this paper a scaling approach for the solution of 2D FE models of electric machines is proposed. This allows a geometrical and stator and rotor resistance scaling as well as a rewinding of a squirrel cage induction machine enabling an efficient numerical optimization. The 2D FEM solutions of a reference machine are calculated by a model based hybrid numeric induction machine simulation approach. In contrast to already known scaling procedures for synchronous machines the FEM solutions of the induction machine are scaled in the stator-current-rotor-frequency-plane and then transformed to the torque- speed-map. This gives the possibility to use a new time scaling factor that is necessary to keep a constant field distribution. The scaling procedure is validated by the finite element method and used in a numerical optimization process for the sizing of an electric vehicle traction drive considering the gear ratio. The results show that the scaling procedure is very accurate, computational very efficient and suitable for the use in machine design optimization.
Virtual machine described in the paper is a runtime program for controllers in small distributed systems. The machine executes intermediate universal code similar to an assembler, compiled in CPDev engineering environment from source programs written in control languages of IEC 61131-3 standard. The machine is implemented as a C program, so it can run on different target platforms. Data formats and commands of the machine code are presented, together with the machine’s Petri-net model, C implementation involving universal and platform-dependent modules, target hardware interface, input/output programming mechanisms, and practical applications.
This paper proposes a comprehensive study on machine listening for localisation of snore sound excitation. Here we investigate the effects of varied frame sizes, and overlap of the analysed audio chunk for extracting low-level descriptors. In addition, we explore the performance of each kind of feature when it is fed into varied classifier models, including support vector machines, k-nearest neighbours, linear discriminant analysis, random forests, extreme learning machines, kernel-based extreme learning machines, multilayer perceptrons, and deep neural networks. Experimental results demonstrate that, wavelet packet transform energy can outperform most other features. A deep neural network trained with subband energy ratios reaches the highest performance achieving an unweighted average recall of 72.8% from four types for snoring.