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Number of results: 13
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Abstract

The machinability and the process parameter optimization of turning operation for 15-5 Precipitation Hardening (PH) stainless steel have been investigated based on the Taguchi based grey approach and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). An L27 orthogonal array was selected for planning the experiment. Cutting speed, depth of cut and feed rate were considered as input process parameters. Cutting force (Fz) and surface roughness (Ra) were considered as the performance measures. These performance measures were optimized for the improvement of machinability quality of product. A comparison is made between the multi-criteria decision making tools. Grey Relational Analysis (GRA) and TOPSIS are used to confirm and prove the similarity. To determine the influence of process parameters, Analysis of Variance (ANOVA) is employed. The end results of experimental investigation proved that the machining performance can be enhanced effectively with the assistance of the proposed approaches.
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Abstract

Automation of machining operations, being result of mass volume production of components, imposes more restrictive requirements concerning mechanical properties of starting materials, inclusive of machinability mainly. In stage of preparation of material, the machinability is influenced by such factors as chemical composition, structure, mechanical properties, plastic working and heat treatment, as well as a factors present during machining operations, as machining type, cutting parameters, material and geometry of cutting tools, stiffness of the system: workpiece – machine tool – fixture and cutting tool. In the paper are presented investigations concerning machinability of the EN AC-AlSi9Cu3(Fe) silumin put to refining, modification and heat treatment. As the parameter to describe starting condition of the alloy was used its tensile strength Rm. Measurement of the machining properties of the investigated alloy was performed using a reboring method with measurement of cutting force, cutting torque and cutting power. It has been determined an effect of the starting condition of the alloy on its machining properties in terms of the cutting power, being indication of machinability of the investigated alloy. The best machining properties (minimal cutting power - Pc=48,3W) were obtained for the refined alloy, without heat treatment, for which the tensile strength Rm=250 MPa. The worst machinability (maximal cutting power Pc=89,0W) was obtained for the alloy after refining, solutioning at temperature 510 o C for 1,5 hour and aged for 5 hours at temperature 175 o C. A further investigations should be connected with selection of optimal parameters of solutioning and ageing treatments, and with their effect on the starting condition of the alloy in terms of improvement of both mechanical properties of the alloy and its machining properties, taking into consideration obtained surface roughness.
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Abstract

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.
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Abstract

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.
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Abstract

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.
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Abstract

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.
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Abstract

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.
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Abstract

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.
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Abstract

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.
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Abstract

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.
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Abstract

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.
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Abstract

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.
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Abstract

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.
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