Search results for: machine tool
2424 One-Class Support Vector Machines for Aerial Images Segmentation
Authors: Chih-Hung Wu, Chih-Chin Lai, Chun-Yen Chen, Yan-He Chen
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Interpretation of aerial images is an important task in various applications. Image segmentation can be viewed as the essential step for extracting information from aerial images. Among many developed segmentation methods, the technique of clustering has been extensively investigated and used. However, determining the number of clusters in an image is inherently a difficult problem, especially when a priori information on the aerial image is unavailable. This study proposes a support vector machine approach for clustering aerial images. Three cluster validity indices, distance-based index, Davies-Bouldin index, and Xie-Beni index, are utilized as quantitative measures of the quality of clustering results. Comparisons on the effectiveness of these indices and various parameters settings on the proposed methods are conducted. Experimental results are provided to illustrate the feasibility of the proposed approach.Keywords: Aerial imaging, image segmentation, machine learning, support vector machine, cluster validity index
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19312423 Hybrid Approach for Country’s Performance Evaluation
Authors: C. Slim
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This paper presents an integrated model, which hybridized data envelopment analysis (DEA) and support vector machine (SVM) together, to class countries according to their efficiency and performance. This model takes into account aspects of multi-dimensional indicators, decision-making hierarchy and relativity of measurement. Starting from a set of indicators of performance as exhaustive as possible, a process of successive aggregations has been developed to attain an overall evaluation of a country’s competitiveness.
Keywords: Artificial neural networks, support vector machine, data envelopment analysis, aggregations, indicators of performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10522422 Tool Wear of Metal Matrix Composite 10wt% AlN Reinforcement Using TiB2 Cutting Tool
Authors: M. S. Said, J. A. Ghani, Che Hassan C. H., N. N. Wan, M. A. Selamat, R. Othman
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Metal matrix composites (MMCs) attract considerable attention as a result from its ability in providing a high strength, high modulus, high toughness, high impact properties, improving wear resistance and providing good corrosion resistance compared to unreinforced alloy. Aluminium Silicon (Al/Si) alloy MMC has been widely used in various industrial sectors such as in transportation, domestic equipment, aerospace, military, construction, etc. Aluminium silicon alloy is an MMC that had been reinforced with aluminium nitrate (AlN) particle and become a new generation material use in automotive and aerospace sector. The AlN is one of the advance material that have a bright prospect in future since it has features such as lightweight, high strength, high hardness and stiffness quality. However, the high degree of ceramic particle reinforcement and the irregular nature of the particles along the matrix material that contribute to its low density is the main problem which leads to difficulties in machining process. This paper examined the tool wear when milling AlSi/AlN Metal Matrix Composite using a TiB2 (Titanium diboride) coated carbide cutting tool. The volume of the AlN reinforced particle was 10% and milling process was carried out under dry cutting condition. The TiB2 coated carbide insert parameters used were at the cutting speed of (230, 300 and 370m/min, feed rate of 0.8, Depth of Cut (DoC) at 0.4m). The Sometech SV-35 video microscope system used to quantify of the tool wear. The result shown that tool life span increasing with the cutting speeds at (370m/min, feed rate of 0.8mm/tooth and DoC at 0.4mm) which constituted an optimum condition for longer tool life lasted until 123.2 mins. Meanwhile, at medium cutting speed which at 300m/m, feed rate of 0.8mm/tooth and depth of cut at 0.4mm we found that tool life span lasted until 119.86 mins while at low cutting speed it lasted in 119.66 mins. High cutting speed will give the best parameter in cutting AlSi/AlN MMCs material. The result will help manufacturers in machining process of AlSi/AlN MMCs materials.
Keywords: AlSi/AlN Metal Matrix Composite milling process, tool wear, TiB2 coated cemented carbide tool.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31862421 Alloying Effect on Hot Workability of M42 High Speed Steel
Authors: Jung-Ho Moon, Tae Kwon Ha
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In the present study, the effect of Si, Al, Ti, Zr, and Nb addition on the microstructure and hot workability of cast M42 tool steels, basically consisting of 1.0C, 0.2Mn, 3.8Cr, 1.5W, 8.5Co, 9.2Mo, and 1.0V in weight percent has been investigated. Tool steels containing Si of 0.25 and 0.5wt.%, Al of 0.06 and 0.12wt.%, Ti of 0.3wt.%, Zr of 0.3wt.%, and Nb of 0.3wt.% were cast into ingots of 140mm ´ 140mm ´ 330mm by vacuum induction melting. After solution treatment at 1150oC for 1.5hr followed by furnace cooling, hot rolling at 1180oC was conducted on the ingots. Addition of titanium, zirconium and niobium was found to retard the decomposition of the eutectic carbides and result in the deterioration of hot workability of the tool steels, while addition of aluminum and silicon showed relatively well decomposed carbide structure and resulted in sound hot rolled plates.
Keywords: High speed steels, alloying elements, eutectic carbides, microstructure, hot workability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26182420 Programmable Logic Controller for Cassava Centrifugal Machine
Authors: R. Oonsivilai, M. Oonsivilai, J. Sanguemrum, N. Thumsirirat, A. Oonsivilai
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Chaiyaphum Starch Co. Ltd. is one of many starch manufacturers that has introduced machinery to aid in manufacturing. Even though machinery has replaced many elements and is now a significant part in manufacturing processes, problems that must be solved with respect to current process flow to increase efficiency still exist. The paper-s aim is to increase productivity while maintaining desired quality of starch, by redesigning the flipping machine-s mechanical control system which has grossly low functional lifetime. Such problems stem from the mechanical control system-s bearings, as fluids and humidity can access into said bearing directly, in tandem with vibrations from the machine-s function itself. The wheel which is used to sense starch thickness occasionally falls from its shaft, due to high speed rotation during operation, while the shaft may bend from impact when processing dried bread. Redesigning its mechanical control system has increased its efficiency, allowing quality thickness measurement while increasing functional lifetime an additional 62 days.Keywords: Control system, Machinery, Measurement, Potato starch
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20902419 Determination of Water Pollution and Water Quality with Decision Trees
Authors: Çiğdem Bakır, Mecit Yüzkat
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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software used in the study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: Preprocessing of the data used, feature detection and classification. We tried to determine the success of our study with different accuracy metrics and the results were presented comparatively. In addition, we achieved approximately 98% success with the decision tree.
Keywords: Decision tree, water quality, water pollution, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2262418 Directional Drilling Optimization by Non-Rotating Stabilizer
Authors: Eisa Noveiri, Adel Taheri Nia
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The Non-Rotating Adjustable Stabilizer / Directional Solution (NAS/DS) is the imitation of a mechanical process or an object by a directional drilling operation that causes a respond mathematically and graphically to data and decision to choose the best conditions compared to the previous mode. The NAS/DS Auto Guide rotary steerable tool is undergoing final field trials. The point-the-bit tool can use any bit, work at any rotating speed, work with any MWD/LWD system, and there is no pressure drop through the tool. It is a fully closed-loop system that automatically maintains a specified curvature rate. The Non–Rotating Adjustable stabilizer (NAS) can be controls curvature rate by exactly positioning and run with the optimum bit, use the most effective weight (WOB) and rotary speed (RPM) and apply all of the available hydraulic energy to the bit. The directional simulator allowed to specify the size of the curvature rate performance errors of the NAS tool and the magnitude of the random errors in the survey measurements called the Directional Solution (DS). The combination of these technologies (NAS/DS) will provide smoother bore holes, reduced drilling time, reduced drilling cost and incredible targeting precision. This simulator controls curvature rate by precisely adjusting the radial extension of stabilizer blades on a near bit Non-Rotating Stabilizer and control process corrects for the secondary effects caused by formation characteristics, bit and tool wear, and manufacturing tolerances.Keywords: non-rotating, Adjustable stabilizer, simulator, Directional Drilling, optimization, Oil Well Drilling
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32652417 Powerful Tool to Expand Business Intelligence: Text Mining
Authors: Li Gao, Elizabeth Chang, Song Han
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With the extensive inclusion of document, especially text, in the business systems, data mining does not cover the full scope of Business Intelligence. Data mining cannot deliver its impact on extracting useful details from the large collection of unstructured and semi-structured written materials based on natural languages. The most pressing issue is to draw the potential business intelligence from text. In order to gain competitive advantages for the business, it is necessary to develop the new powerful tool, text mining, to expand the scope of business intelligence. In this paper, we will work out the strong points of text mining in extracting business intelligence from huge amount of textual information sources within business systems. We will apply text mining to each stage of Business Intelligence systems to prove that text mining is the powerful tool to expand the scope of BI. After reviewing basic definitions and some related technologies, we will discuss the relationship and the benefits of these to text mining. Some examples and applications of text mining will also be given. The motivation behind is to develop new approach to effective and efficient textual information analysis. Thus we can expand the scope of Business Intelligence using the powerful tool, text mining.Keywords: Business intelligence, document warehouse, text mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26462416 A Study on the Accelerated Life Cycle Test Method of the Motor for Home Appliances by Using Acceleration Factor
Authors: Youn-Sung Kim, Mi-Sung Kim, Jae-Kun Lee
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This paper deals with the accelerated life cycle test method of the motor for home appliances that demand high reliability. Life Cycle of parts in home appliances also should be 10 years because life cycle of the home appliances such as washing machine, refrigerator, TV is at least 10 years. In case of washing machine, the life cycle test method of motor is advanced for 3000 cycle test (1cycle = 2hours). However, 3000 cycle test incurs loss for the time and cost. Objectives of this study are to reduce the life cycle test time and the number of test samples, which could be realized by using acceleration factor for the test time and reduction factor for the number of sample.
Keywords: Accelerated life cycle test, motor reliability test, motor for washing machine, BLDC motor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35782415 Importance of Simulation in Manufacturing
Authors: F. Hosseinpour, H. Hajihosseini
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Simulation is a very helpful and valuable work tool in manufacturing. It can be used in industrial field allowing the system`s behavior to be learnt and tested. Simulation provides a low cost, secure and fast analysis tool. It also provides benefits, which can be reached with many different system configurations. Topics to be discussed include: Applications, Modeling, Validating, Software and benefits of simulation. This paper provides a comprehensive literature review on research efforts in simulation.Keywords: Manufacturing, modeling, simulation, training.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 79882414 Experimental Investigation on Over-Cut in Ultrasonic Machining of WC-Co Composite
Authors: Ravinder Kataria, Jatinder Kumar, B. S. Pabla
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Ultrasonic machining is one of the most widely used non-traditional machining processes for machining of materials that are relatively brittle, hard, and fragile such as advanced ceramics, refractories, crystals, quartz etc. Present article has been targeted at investigating the impact of different experimental conditions (power rating, cobalt content, tool material, thickness of work piece, tool geometry, and abrasive grit size) on over cut in ultrasonic drilling of WC-Co composite material. Taguchi’s L-36 orthogonal array has been employed for conducting the experiments. Significant factors have been identified using analysis of variance (ANOVA) test. The experimental results revealed that abrasive grit size and tool material are most significant factors for over cut.
Keywords: ANOVA, Abrasive grit size, Taguchi, WC-Co, ultrasonic machining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16772413 Expression of Security Policy in Medical Systems for Electronic Healthcare Records
Authors: Nathan C. Lea, Tony Austin, Stephen Hailes, Dipak Kalra
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This paper introduces a tool that is being developed for the expression of information security policy controls that govern electronic healthcare records. By reference to published findings, the paper introduces the theory behind the use of knowledge management for automatic and consistent security policy assertion using the formalism called the Secutype; the development of the tool and functionality is discussed; some examples of Secutypes generated by the tool are provided; proposed integration with existing medical record systems is described. The paper is concluded with a section on further work and critique of the work achieved to date.
Keywords: Information Security Policy, Electronic Healthcare Records, Knowledge Management, Archetypes, Secutypes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13402412 Flexible Manufacturing System
Authors: Peter Kostal, Karol Velisek
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Flexible manufacturing system is a system that is able to respond to changed conditions. In general, this flexibility is divided into two key categories and several subcategories. The first category is the so called machine flexibility which enables to make various products by the given machinery. The second category is routing flexibility enabling to execute the same operation by various machines. Flexible manufacturing systems usually consist of three main parts: CNC machine tools, transport system and control system. A higher level of flexible manufacturing systems is represented by the so called intelligent manufacturing systems.
Keywords: drawing-free manufacturing, flexible manufacturing system, industrial robot, material flow.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 49432411 Discussing Embedded versus Central Machine Learning in Wireless Sensor Networks
Authors: Anne-Lena Kampen, Øivind Kure
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Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.
Keywords: Central ML, embedded machine learning, energy consumption, local ML, Wireless Sensor Networks, WSN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8142410 Advantages of a New Manufacturing Facility for the Production of Nanofiber
Authors: R. Knizek, D. Karhankova
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The production of nanofibers and the machinery for their production is a current issue. The pioneer, in the industrial production of nanofibers, is the machinery with the sales descriptions NanospiderTM from the company Elmarco, which came into being in 2008. Most of the production facilities, like NanospiderTM, use electrospinning. There are also other methods of industrial production of nanofibers, such as the centrifugal spinning process, which is used by FibeRio Technology Corporation. However, each method and machine has its advantages, but also disadvantages and that is the reason why a new machine called as Nanomachine, which eliminates the disadvantages of other production facilities producing nanofibers, has been developed.
Keywords: Nanomachine, nanospider, spinning slat, electrospinning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15132409 Fuzzy Rules Generation and Extraction from Support Vector Machine Based on Kernel Function Firing Signals
Authors: Prasan Pitiranggon, Nunthika Benjathepanun, Somsri Banditvilai, Veera Boonjing
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Our study proposes an alternative method in building Fuzzy Rule-Based System (FRB) from Support Vector Machine (SVM). The first set of fuzzy IF-THEN rules is obtained through an equivalence of the SVM decision network and the zero-ordered Sugeno FRB type of the Adaptive Network Fuzzy Inference System (ANFIS). The second set of rules is generated by combining the first set based on strength of firing signals of support vectors using Gaussian kernel. The final set of rules is then obtained from the second set through input scatter partitioning. A distinctive advantage of our method is the guarantee that the number of final fuzzy IFTHEN rules is not more than the number of support vectors in the trained SVM. The final FRB system obtained is capable of performing classification with results comparable to its SVM counterpart, but it has an advantage over the black-boxed SVM in that it may reveal human comprehensible patterns.Keywords: Fuzzy Rule Base, Rule Extraction, Rule Generation, Support Vector Machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18872408 Quranic Braille System
Authors: Abdallah M. Abualkishik, Khairuddin Omar
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This article concerned with the translation of Quranic verses to Braille symbols, by using Visual basic program. The system has the ability to translate the special vibration for the Quran. This study limited for the (Noun + Scoon) vibrations. It builds on an existing translation system that combines a finite state machine with left and right context matching and a set of translation rules. This allows to translate the Arabic language from text to Braille symbols after detect the vibration for the Quran verses.Keywords: Braille, Quran vibration, Finite State Machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30482407 Tool Condition Monitoring of Ceramic Inserted Tools in High Speed Machining through Image Processing
Authors: Javier A. Dominguez Caballero, Graeme A. Manson, Matthew B. Marshall
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Cutting tools with ceramic inserts are often used in the process of machining many types of superalloy, mainly due to their high strength and thermal resistance. Nevertheless, during the cutting process, the plastic flow wear generated in these inserts enhances and propagates cracks due to high temperature and high mechanical stress. This leads to a very variable failure of the cutting tool. This article explores the relationship between the continuous wear that ceramic SiAlON (solid solutions based on the Si3N4 structure) inserts experience during a high-speed machining process and the evolution of sparks created during the same process. These sparks were analysed through pictures of the cutting process recorded using an SLR camera. Features relating to the intensity and area of the cutting sparks were extracted from the individual pictures using image processing techniques. These features were then related to the ceramic insert’s crater wear area.Keywords: Ceramic cutting tools, high speed machining, image processing, tool condition monitoring, tool wear.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21752406 Optimization of the Dental Direct Digital Imaging by Applying the Self-Recognition Technology
Authors: Mina Dabirinezhad, Mohsen Bayat Pour, Amin Dabirinejad
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This paper is intended to introduce the technology to solve some of the deficiencies of the direct digital radiology. Nowadays, digital radiology is the latest progression in dental imaging, which has become an essential part of dentistry. There are two main parts of the direct digital radiology comprised of an intraoral X-ray machine and a sensor (digital image receptor). The dentists and the dental nurses experience afflictions during the taking image process by the direct digital X-ray machine. For instance, sometimes they need to readjust the sensor in the mouth of the patient to take the X-ray image again due to the low quality of that. Another problem is, the position of the sensor may move in the mouth of the patient and it triggers off an inappropriate image for the dentists. It means that it is a time-consuming process for dentists or dental nurses. On the other hand, taking several the X-ray images brings some problems for the patient such as being harmful to their health and feeling pain in their mouth due to the pressure of the sensor to the jaw. The author provides a technology to solve the above-mentioned issues that is called “Self-Recognition Direct Digital Radiology” (SDDR). This technology is based on the principle that the intraoral X-ray machine is capable to diagnose the location of the sensor in the mouth of the patient automatically. In addition, to solve the aforementioned problems, SDDR technology brings out fewer environmental impacts in comparison to the previous version.
Keywords: Dental direct digital imaging, digital image receptor, digital x-ray machine, and environmental impacts.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5822405 Normal and Peaberry Coffee Beans Classification from Green Coffee Bean Images Using Convolutional Neural Networks and Support Vector Machine
Authors: Hira Lal Gope, Hidekazu Fukai
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The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.
Keywords: Convolutional neural networks, coffee bean, peaberry, sorting, support vector machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15182404 Concept Indexing using Ontology and Supervised Machine Learning
Authors: Rossitza M. Setchi, Qiao Tang
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Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.Keywords: Concepts, indexing, machine learning, ontology, tagging.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16662403 Integration of Virtual Learning of Induction Machines for Undergraduates
Authors: Rajesh Kumar, Puneet Aggarwal
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In context of understanding problems faced by undergraduate students while carrying out laboratory experiments dealing with high voltages, it was found that most of the students are hesitant to work directly on machine. The reason is that error in the circuitry might lead to deterioration of machine and laboratory instruments. So, it has become inevitable to include modern pedagogic techniques for undergraduate students, which would help them to first carry out experiment in virtual system and then to work on live circuit. Further advantages include that students can try out their intuitive ideas and perform in virtual environment, hence leading to new research and innovations. In this paper, virtual environment used is of MATLAB/Simulink for three-phase induction machines. The performance analysis of three-phase induction machine is carried out using virtual environment which includes Direct Current (DC) Test, No-Load Test, and Block Rotor Test along with speed torque characteristics for different rotor resistances and input voltage, respectively. Further, this paper carries out computer aided teaching of basic Voltage Source Inverter (VSI) drive circuitry. Hence, this paper gave undergraduates a clearer view of experiments performed on virtual machine (No-Load test, Block Rotor test and DC test, respectively). After successful implementation of basic tests, VSI circuitry is implemented, and related harmonic distortion (THD) and Fast Fourier Transform (FFT) of current and voltage waveform are studied.
Keywords: Block rotor test, DC test, no-load test, virtual environment, VSI.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8772402 Evaluating the Tool Wear Rate in Ultrasonic Machining of Titanium using Design of Experiments Approach
Authors: Jatinder Kumar, Vinod Kumar
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Ultrasonic machining (USM) is a non-traditional machining process being widely used for commercial machining of brittle and fragile materials such as glass, ceramics and semiconductor materials. However, USM could be a viable alternative for machining a tough material such as titanium; and this aspect needs to be explored through experimental research. This investigation is focused on exploring the use of ultrasonic machining for commercial machining of pure titanium (ASTM Grade-I) and evaluation of tool wear rate (TWR) under controlled experimental conditions. The optimal settings of parameters are determined through experiments planned, conducted and analyzed using Taguchi method. In all, the paper focuses on parametric optimization of ultrasonic machining of pure titanium metal with TWR as response, and validation of the optimized value of TWR by conducting confirmatory experiments.Keywords: Ultrasonic machining, titanium, tool wear rate
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24972401 A Cognitive Model of Character Recognition Using Support Vector Machines
Authors: K. Freedman
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In the present study, a support vector machine (SVM) learning approach to character recognition is proposed. Simple feature detectors, similar to those found in the human visual system, were used in the SVM classifier. Alphabetic characters were rotated to 8 different angles and using the proposed cognitive model, all characters were recognized with 100% accuracy and specificity. These same results were found in psychiatric studies of human character recognition.Keywords: Character recognition, cognitive model, support vector machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18672400 An Experimental Study and Influence of BHF and Die Radius in Deep Drawing Process on the Springback
Authors: A. Soualem
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A lot of research made during these last 15 years showed that the quantification of the springback has a significant role in the industry of sheet metal forming. These studies were made with the objective of finding techniques and methods to minimize or completely avoid this permanent physical variation. Moreover, the use of steel and aluminum alloys in the car industry and aviation poses every day the problem of the springback. The determination in advance of the quantity of the springback allows consequently the design and manufacture of the tool. The aim of this paper is to study experimentally the influence of the blank holder force BHF and the radius of curvature of the die on the springback and their influence on the strain in various zone of specimen. The original of our purpose consist on tests which are ensured by adapting a U-type stretching-bending device on a tensile testing machine, where we studied and quantified the variation of the springback according to displacement.Keywords: Blank holder force, Deep-Drawing, Die radius, Forming, Springback.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16882399 Improvement Approach on Rotor Time Constant Adaptation with Optimum Flux in IFOC for Induction Machines Drives
Authors: S. Grouni, R. Ibtiouen, M. Kidouche, O. Touhami
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Induction machine models used for steady-state and transient analysis require machine parameters that are usually considered design parameters or data. The knowledge of induction machine parameters is very important for Indirect Field Oriented Control (IFOC). A mismatched set of parameters will degrade the response of speed and torque control. This paper presents an improvement approach on rotor time constant adaptation in IFOC for Induction Machines (IM). Our approach tends to improve the estimation accuracy of the fundamental model for flux estimation. Based on the reduced order of the IM model, the rotor fluxes and rotor time constant are estimated using only the stator currents and voltages. This reduced order model offers many advantages for real time identification parameters of the IM.Keywords: Indirect Field Oriented Control (IFOC), InductionMachine (IM), Rotor Time Constant, Parameters ApproachAdaptation. Optimum rotor flux.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16942398 Testing of DISAL D240 and D420 Ceramic Tool Materials with an Interrupted Cut Simulator
Authors: Robert Cep, Marek Sadilek, Lenka Ocenasova, Josef Brychta, Michal Hatala, Branimir Barisic
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This paper presents a solution for ceramic cutting tools availability in interrupted machining. Experiments were performed on a special fixture – the interrupted cut simulator. This fixture was constructed at our Department of Machining and Assembly within the scope of a project by the Czech Science Foundation. The goals of the tests were to contribute to the wider usage of these cutting materials in machining, especially in interrupted machining. Through the centuries, producers of ceramic cutting tools have taken big steps forward. Namely, increasing durability in maintaining high levels of strength and hardness lends an advantage. Some producers of these materials advise cutting inserts for interrupted machining at the present time [1, 2].
Keywords: Ceramic cutting tool, cutting tool tests, interrupted cutting, machining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15102397 An Experimentally Validated Thermo- Mechanical Finite Element Model for Friction Stir Welding in Carbon Steels
Authors: A. H. Kheireddine, A. A. Khalil, A. H. Ammouri, G. T. Kridli, R. F. Hamade
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Solidification cracking and hydrogen cracking are some defects generated in the fusion welding of ultrahigh carbon steels. However, friction stir welding (FSW) of such steels, being a solid-state technique, has been demonstrated to alleviate such problems encountered in traditional welding. FSW include different process parameters that must be carefully defined prior processing. These parameters included but not restricted to: tool feed, tool RPM, tool geometry, tool tilt angle. These parameters form a key factor behind avoiding warm holes and voids behind the tool and in achieving a defect-free weld. More importantly, these parameters directly affect the microstructure of the weld and hence the final mechanical properties of weld. For that, 3D finite element (FE) thermo-mechanical model was developed using DEFORM 3D to simulate FSW of carbon steel. At points of interest in the joint, tracking is done for history of critical state variables such as temperature, stresses, and strain rates. Typical results found include the ability to simulate different weld zones. Simulations predictions were successfully compared to experimental FSW tests. It is believed that such a numerical model can be used to optimize FSW processing parameters to favor desirable defect free weld with better mechanical properties.
Keywords: Carbon Steels, DEFORM 3D, FEM, Friction stir welding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25602396 The Influence of Preprocessing Parameters on Text Categorization
Authors: Jan Pomikalek, Radim Rehurek
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Text categorization (the assignment of texts in natural language into predefined categories) is an important and extensively studied problem in Machine Learning. Currently, popular techniques developed to deal with this task include many preprocessing and learning algorithms, many of which in turn require tuning nontrivial internal parameters. Although partial studies are available, many authors fail to report values of the parameters they use in their experiments, or reasons why these values were used instead of others. The goal of this work then is to create a more thorough comparison of preprocessing parameters and their mutual influence, and report interesting observations and results.
Keywords: Text categorization, machine learning, electronic documents, classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15642395 Genetic Folding: Analyzing the Mercer-s Kernels Effect in Support Vector Machine using Genetic Folding
Authors: Mohd A. Mezher, Maysam F. Abbod
Abstract:
Genetic Folding (GF) a new class of EA named as is introduced for the first time. It is based on chromosomes composed of floating genes structurally organized in a parent form and separated by dots. Although, the genotype/phenotype system of GF generates a kernel expression, which is the objective function of superior classifier. In this work the question of the satisfying mapping-s rules in evolving populations is addressed by analyzing populations undergoing either Mercer-s or none Mercer-s rule. The results presented here show that populations undergoing Mercer-s rules improve practically models selection of Support Vector Machine (SVM). The experiment is trained multi-classification problem and tested on nonlinear Ionosphere dataset. The target of this paper is to answer the question of evolving Mercer-s rule in SVM addressed using either genetic folding satisfied kernel-s rules or not applied to complicated domains and problems.Keywords: Genetic Folding, GF, Evolutionary Algorithms, Support Vector Machine, Genetic Algorithm, Genetic Programming, Multi-Classification, Mercer's Rules
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