scholarly journals Brushless Electric Machines with Axial Magnetic Flux: Analysis and Synthesis

2021 ◽  
Author(s):  
Sergey Gandzha ◽  
Dmitry Gandzha
Keyword(s):  
Magnetic Flux ◽  
Computer Aided Design ◽  
Electric Machines ◽  
Engineering Practice ◽  
Flux Analysis ◽  
Electromagnetic Moment ◽  
Electromagnetic Power ◽  
Analysis And Synthesis ◽  
Aided Design

An analysis of electric machines with axial magnetic flux is given. First, the effect of commutation on the electromagnetic moment and electromagnetic power is analyzed. Two types of discrete switching are considered. The analysis is performed for an arbitrary number of phases. The first type of switching involves disabling one phase for the duration of switching. The second type of switching involves the operation of all phases in the switching interval. The influence of the pole arc and the number of phases on the electromagnetic moment and electromagnetic power is investigated. The conclusion is made about the advantage of the second type of switching. It is recommended to increase the number of phases. Next, the classification of the main structures of the axial machine is carried out. Four main versions are defined. For each variant, the equation of the electromagnetic moment and electromagnetic power is derived. This takes into account the type of commutation. The efficiency of the selected structures is analyzed. The comparative analysis is tabulated for choosing the best option. The table is convenient for engineering practice. This chapter forms the basis for computer-aided design of this class of machines.

Magnetic Flux Analysis for the Condition Monitoring of Electric Machines: A Review

2021 ◽  
pp. 1-1
Author(s):  
Israel Zamudio-Ramirez ◽  
Roque A Alfredo Osornio-Rios ◽  
Jose Alfonso Antonino-Daviu ◽  
Hubert Razik ◽  
Rene de Jesus Romero-Troncoso
Keyword(s):  
Magnetic Flux ◽  
Condition Monitoring ◽  
Electric Machines ◽  
Flux Analysis

scholarly journals A computer-aided design mammography screening system for detection and classification of microcalcifications

2000 ◽  
Vol 60 (1) ◽  
pp. 29-57 ◽  
Author(s):  
San-Kan Lee ◽  
Chien-Shun Lo ◽  
Chuin-Mu Wang ◽  
Pau-Choo Chung ◽  
Chein-I Chang ◽  
...  
Keyword(s):  
Mammography Screening ◽  
Computer Aided Design ◽  
Screening System ◽  
Computer Aided ◽  
Aided Design

Reconstruction of Trimmed NURBS Surfaces for Gap-Free Intersections

2020 ◽  
Vol 20 (5) ◽  
Author(s):  
Benjamin Urick ◽  
Richard H. Crawford ◽  
Thomas J. R. Hughes ◽  
Elaine Cohen ◽  
Richard F. Riesenfeld
Keyword(s):  
Computer Aided Design ◽  
Engineering Practice ◽  
Global Parameter ◽  
Trimmed Surfaces ◽  
File Formats ◽  
Modern Engineering ◽  
Computer Aided ◽  
Step Algorithm ◽  
Aided Design ◽  
User Knowledge

Abstract The modern engineering technologies of computer-aided design (CAD), computer-aided engineering (CAE), and computer-aided manufacturing (CAM) are ubiquitous in engineering practice. They are focused on creating, analyzing, and fabricating engineering artifacts represented as geometric models. Historically, these technologies developed independently, with different geometric representations that are customized to the needs of the technology. As a result, the combined use of these technologies has led to differences in data structures, file formats, and user knowledge and practice, requiring translation of representations between systems to support interoperability. Complicating this situation is the approximate nature of modeling operations in CAD systems, which can result in gaps at the boundary curves between mating trimmed surfaces of a model. The research presented here is aimed at removing the gaps between trimmed surfaces, resulting in a “watertight” model that is suitable for use directly by downstream applications. A three-step algorithm is presented that includes analysis of the parametric space of the trimming curves, reparameterization to create a global parameter space, and reconstruction of the intersecting surfaces to ensure continuity at the trimming curve.

Computer aided design of electromechanical transducer of gated traction motor by using modern software

2016 ◽  
pp. 72-79
Author(s):  
Roman Proshutinsky ◽  
Oleg Kolodkin
Keyword(s):  
Computer Aided Design ◽  
Magnetic Circuit ◽  
Electric Machines ◽  
Traction Motor ◽  
Traction Drive ◽  
Cad System ◽  
Electromechanical Transducer ◽  
Electric Traction ◽  
Aided Design ◽  
Femm Software

Objective: To develop a system of computer aided design for electrical traction drive complex, as a component of CAD for electric rolling stock. Modern approach for electrical traction drive complex design means the development of assembly of interconnected systems, such as electrical traction motor, transducer, control system, etc. The most striking instance of such an assembly is gated traction motor, that is somehow in-between electric machines and electric drives. It is usefull to start the developing of CAD gated traction motor by developing the CAD system for electromechanical transducer of gated traction motor. Methods: In the base of CAD system under development there is a technology of design of electromechanical transducer of gated traction motor. At the stage of electromechanical transducer magnetic circuit calculation the software for simulation of magnetic fields by finite elements method was used. Results: The paper suggests the structure diagram of CAD system for electromechanical transducer of gated traction motor. Calculating software language is Octave. The paper provides the results of magnetic field calculations for electromechanical transducer of gated traction motor FEMM software for finite-element simulation. Based on the results of magnetic field calculations the curve of electromechanical transducer energizing is plot. Also the practicability of FEMM software implementation at the design stage of magnetic circuit is confirmed. Practical importance: Obtained results are useful for creation of educational and research system for CAD for electric traction drive complex. Development of CAD system for gated traction motor will allow to master methods and approaches of design for electric machines and semiconductor complexes of electric traction drives in general.

scholarly journals Synthetica 2.0: Software for the Synthesis of Constrained Serial Chains

2004 ◽  
Author(s):  
Alba Perez ◽  
Hai-Jun Su ◽  
J. Michael McCarthy
Keyword(s):  
Computer Aided Design ◽  
Visualization Analysis ◽  
Task Definition ◽  
Computer Aided ◽  
Analysis And Synthesis ◽  
Spatial Linkages ◽  
Aided Design ◽  
Serial Chains

A spatial linkage is defined by a workpiece supported by one or more serial chains. We say that the spatial linkage can perform a given task when this task belongs to its workspace. A task can be specified as a discrete set of positions or as a set of curves or surfaces. Spatial serial chains can be synthesized to perform specified tasks, and combined to form more complicated linkages. Recently we developed Synthetica 1.0, a Java-based architecture for the computer-aided-design of spatial linkages that contains task definition and visualization, and linkage visualization, analysis and synthesis modules. In this paper, we present the new version, Synthetica 2.0. Among other additions, the new version includes task interpolation, a selection matrix, a generic synthesizer and several specialized synthesis procedures for constrained spatial linkages.

scholarly journals Characteristic Identification Methodology for 2D Sheet Metal Components

2019 ◽  
Vol 9 (2S4) ◽  
pp. 448-452
Keyword(s):  
Computer Aided Design ◽  
Computer Assisted ◽  
Production Environment ◽  
Feature Identification ◽  
Geometric Information ◽  
Wire Frame ◽  
Multiple Feature ◽  
Boundary Functions ◽  
Aided Design

In the computer-integrated production environment, computer-assisted process planning is a key area which analyses the Computer aided Design server collects information about design and converts it into the necessary information about manufacturing. To identify 2D sheet shearing operations from the nested architecture provided by a wire frame template, a feature identification procedure has been suggested. Basically, the method uses geometric data to determine different groups of objects. Entity groups are categorized into a number of features for raw resources, a set of boundary features, and a set of interior features. There seems to be a special classification of the feature functions inclusion to both the set of boundary functions. Components (i.e. boundary elements set together with their inside feature set components) are lexicographically arranged. Based on the suggested categorization for shearing practices and using multiple feature sets, processing features were defined. The technique listed above, definitions are explained along with its principles. This is performed in the C environment and from the DXF output directory of AutoCAD geometric information is retrieved..

scholarly journals An Efficient ensemble of Brain Tumour Segmentation and Classification using Machine Learning and Deep Learning based Inception Networks

2021 ◽  
Vol 12 (2) ◽  
pp. 987-998
Author(s):  
R. Aruna Kirithika, Et. al.
Keyword(s):  
Deep Learning ◽  
Computer Aided Design ◽  
Tumour Segmentation ◽  
Area Of Interest ◽  
Proposed Model ◽  
Diagnosis And Classification ◽  
Almost All ◽  
Aided Design ◽  
Brain Tumour Segmentation

In recent times, Brain Tumor (BT) has become a common phenomenon affecting almost all age group of people. Identification of this deadly disease using computer tomography, magnetic resonance imaging are very popular now-a-days. Developing a Computer Aided Design (CAD) tool for diagnosis and classification of BT has become vital. This paper focuses on designing a tool for diagnosis and classification of BT using Deep Learning (DL) models, which involves a series of steps via acquiring (CT) image, pre-processing, segmenting and classifying to identify the type of tumor using SIFT with DL based Inception network model. The proposed model uses fuzzy C means algorithm for segmenting area of interest from the BT image acquired. Techniques like Gaussian Naïve Bayes (GNB) and logistic regression (LR) are used for classification processes. To ascertain all the techniques for its efficiency a benchmark dataset was used. The simulation outcome ensured that the performance of the proposed method with maximum sensitivity of 100%, specificity of 97.41% and accuracy of 97.96%.

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