Comparison of Artificial Immune System and Particle Swarm Optimization Techniques for Error Optimization of Machine Vision Based Tool Movements

Mahapatra, P.K. and Sethi, Spardha and Kumar, Amod (2015) Comparison of Artificial Immune System and Particle Swarm Optimization Techniques for Error Optimization of Machine Vision Based Tool Movements. Journal of The Institution of Engineers (India): Series C. ISSN 2250-0545

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Official URL: http://link.springer.com/article/10.1007%2Fs40032-...

Abstract

In conventional tool positioning technique, sensors embedded in the motion stages provide the accurate tool position information. In this paper, a machine vision based system and image processing technique for motion measurement of lathe tool from two-dimensional sequential images captured using charge coupled device camera having a resolution of 250 microns has been described. An algorithm was developed to calculate the observed distance travelled by the tool from the captured images. As expected, error was observed in the value of the distance traversed by the tool calculated from these images. Optimization of errors due to machine vision system, calibration, environmental factors, etc. in lathe tool movement was carried out using two soft computing techniques, namely, artificial immune system (AIS) and particle swarm optimization (PSO). The results show better capability of AIS over PSO.

Item Type: Article
Uncontrolled Keywords: Error optimization; Artificial immune system; CLONALG algorithm; PSO technique; Image processing
Subjects: CSIO > Medical Instrumentation
Depositing User: Ms. Jyotsana
Date Deposited: 09 Aug 2018 12:07
Last Modified: 09 Aug 2018 12:07
URI: http://csioir.csio.res.in/id/eprint/529

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