Neurofuzzy Implementation in Smart Toolpost To Improve Performance

Neurofuzzy Implementation in Smart Toolpost To Improve Performance

Dr. Maki K. Rashid

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Sultan Qaboos University

Neurofuzzy Implementation in Smart Toolpost To Improve Performance

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Abstract

Machining is a complex process that requires a high degree of precision with tight geometrical tolerance and surface finish. Those are confronted by the existence of vibration in the turning machine tool. Overcoming a micro level vibration of a cutting tool using smart materials can save old machines and enhance flexibility in designing new generations of machine tools. Using smart materials to resolve such problems represent one of the challenges in this area. In this work the transient solution for tool tip displacement, the pulse width modulation (PWM) technique is implemented for smart material activation to compensate for the radial disturbing cutting forces. A Neurofuzzy algorithm is developed to control the actuator voltage level to improve dynamic performance. The deployment of the finite element method in this work as a dynamic model is to investigate the ability of the in intelligent techniques in improving cutting tool accuracies. The influence of minimum number of PWM cycles with each disturbing force cycle is investigated in controlling the tool error growth. Toolpost structural force excitation due to the PWM cycles was not given adequate attention in previous publications. A methodology is developed to utilize toolpost static force-displacement diagram to obtain required activation voltage to shrink error under different dynamic operating conditions using neurofuzzy.

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. Maki K. Rashid. 2011. \u201cNeurofuzzy Implementation in Smart Toolpost To Improve Performance\u201d. Global Journal of Research in Engineering - A : Mechanical & Mechanics GJRE-A Volume 11 (GJRE Volume 11 Issue A7): .

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GJRE Volume 11 Issue A7
Pg. 1- 10

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Keywords

Cutting tool Neurofuzzy Smart Material Tool vibration Vibration suppression

Submission ReceivedSeptember 28, 2011
Peer Review Double Blind
Handling Editor
Accepted October 24, 2011
Published November 8, 2011

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v1.2

Issue date

December 23, 2011

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Article Matrices

Total Score: 126

Country: Oman

Subject: Global Journal of Research in Engineering - A : Mechanical & Mechanics

Authors: Dr. Maki K. Rashid (PhD/Dr. count: 1)

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Publish Date: 2011 12, Fri

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Total Views: 5400

Total Downloads: 2821

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