Technical Briefs

A System Framework With Online Monitoring and Evaluation for Design Evolution of Engineering Systems

[+] Author and Article Information
L. B. Gamage

Industrial Automation Laboratory, Department of Mechanical Engineering, The University of British Columbia, Vancouver, BC, V6T 1Z4, Canada

C. W. de Silva

Industrial Automation Laboratory, Department of Mechanical Engineering, The University of British Columbia, Vancouver, BC, V6T 1Z4, Canadadesilva@mech.ubc.ca

J. Comput. Inf. Sci. Eng 10(3), 034501 (Sep 01, 2010) (6 pages) doi:10.1115/1.3462919 History: Received July 07, 2009; Revised March 04, 2010; Published September 01, 2010; Online September 01, 2010

This paper presents a methodology for the design evolution of engineering systems, with a mechatronic emphasis. The developed approach specifically integrates machine health monitoring and an expert system and carries out the design evolution of a multidomain dynamic system using bond graph modeling and genetic programming. The evolution of a bond graph model of a mechatronic system through genetic programming enables the exploration of the design space, thereby generating a global optimum design solution in an automated manner. Domain knowledge and expertise are used to control the design exploration and to restrict it only to a meaningful design space. As an illustrative example, the developed methodology is applied to redesign the electrohydraulic manipulator of an existing industrial fish processing machine.

Copyright © 2010 by American Society of Mechanical Engineers
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Figure 1

Schematic diagram of the evolutionary design system

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Figure 2

Growth of a bond graph. (a) Insertion of an R element to a junction. (b) Insertion of a 0 junction in a bond.

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Figure 3

The algorithm of design evolution

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Figure 4

Fish processing machine

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Figure 5

Time response of cutter assembly

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Figure 6

Block diagram of the hydraulic system

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Figure 7

(a) Servovalve. (b) Hydraulic actuator.

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Figure 8

Responses for (a) system identification and (b) design evolution

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Figure 9

Embryo model with modifiable sites in the servovalve

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Figure 10

Evolved model with the identified sites

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Figure 11

Schematic representation of the computation of the design feasibility index




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