Classification Decision of Mechanical Drive Types Using LVQ Neural Classifier in Conceptual Design

Rui Feng Bo

doi:10.4028/www.scientific.net/AMM.101-102.614

Paper Titles

The Study on the Torque Carrying Capacity of the Joint Bearing Six-Hole Style Laminated Membrane Coupling
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Research on Web-Based Reverse Engineering Service Center
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Improved Mu Method with Mixed Perturbation to Dynamic Pressure
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A Project-Driven E-Design System for Product Development Process Modeling
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Classification Decision of Mechanical Drive Types Using LVQ Neural Classifier in Conceptual Design
p.614

Study on the Method of Expressing the Pitch Curve of Non-Circular Gear Based on NURBS Curve
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Water Lubricated Bearing Lubrication Model Based on Multilayer Gridding
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The Application of Tool Radius Compensation in NC Processing
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Calculation of Dimension Chain through AUTOCAD Secondary Development Technique Based on Dimension Tracking Method
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 101-102Classification Decision of Mechanical Drive Types...

Classification Decision of Mechanical Drive Types Using LVQ Neural Classifier in Conceptual Design

Abstract:

In conceptual design of mechanical system, selecting an appropriate mechanical drive type that meets design requirements is a critical problem. To tackle it, a novel classification decision approach to drive type selection is presented, which employs LVQ neural network as classifier to recognize a satisfactory drive from a range of drive types. This recognition process includes five stages: (1) capturing linguistic expression values of character factor for typical drives; (2) digitizing linguistic expression values and extracting features of drives; (3) constructing the structure of a LVQ neural network; (4) training this network with the feature data of character factor set; (5) identifying an appropriate drive type according to the input data using the trained neural network. This proposed approach capitalizes on the benefits of LVQ neural network to acquire domain knowledge and implement classification and decision. Hence at some extent the process of conceptual design can be simplified and the rationality of the decision can be greatly improved.