Optimum drill bit selection by using bit images and mathematical investigation

This study is designed to consider the two important yet often neglected factors, which are factory recommendation and bit features, in optimum bit selection. Image processing techniques have been used to consider the bit features. A mathematical equation, which is derived from a neural network mode...

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Main Authors: Momeni, M., Ridha, S., Hosseiniz, S.J., Liu, X., Atashnezhad, A., Ghaheri, S.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.19294 /
Published: Materials and Energy Research Center 2017
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85036639979&doi=10.5829%2fije.2017.30.11b.24&partnerID=40&md5=6bc021c8c2756b8009f5686ec5f44413
http://eprints.utp.edu.my/19294/
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spelling utp-eprints.192942018-05-03T02:10:13Z Optimum drill bit selection by using bit images and mathematical investigation Momeni, M. Ridha, S. Hosseiniz, S.J. Liu, X. Atashnezhad, A. Ghaheri, S. This study is designed to consider the two important yet often neglected factors, which are factory recommendation and bit features, in optimum bit selection. Image processing techniques have been used to consider the bit features. A mathematical equation, which is derived from a neural network model, is used for drill bit selection to obtain the bit's maximum penetration rate that corresponds to the optimum parameters for drilling. At the end, the bit with the maximum penetration rate is chosen. The results of this study showed that bit pattern can be inserted in the calculation through a proper bit image processing technique. This is to ensure that each unique bit can be discriminated from other bits. The values of mean square error and coefficient of determination (R2) were respectively found as 0.0037 and 0.9473, for the rate of penetration model. The image processing techniques were used to extract the bit features. The artificial neural network black box was converted to white box in order to extract a mathematical equation and visibility of the model. Materials and Energy Research Center 2017 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85036639979&doi=10.5829%2fije.2017.30.11b.24&partnerID=40&md5=6bc021c8c2756b8009f5686ec5f44413 Momeni, M. and Ridha, S. and Hosseiniz, S.J. and Liu, X. and Atashnezhad, A. and Ghaheri, S. (2017) Optimum drill bit selection by using bit images and mathematical investigation. International Journal of Engineering, Transactions B: Applications, 30 (11). pp. 1807-1813. http://eprints.utp.edu.my/19294/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description This study is designed to consider the two important yet often neglected factors, which are factory recommendation and bit features, in optimum bit selection. Image processing techniques have been used to consider the bit features. A mathematical equation, which is derived from a neural network model, is used for drill bit selection to obtain the bit's maximum penetration rate that corresponds to the optimum parameters for drilling. At the end, the bit with the maximum penetration rate is chosen. The results of this study showed that bit pattern can be inserted in the calculation through a proper bit image processing technique. This is to ensure that each unique bit can be discriminated from other bits. The values of mean square error and coefficient of determination (R2) were respectively found as 0.0037 and 0.9473, for the rate of penetration model. The image processing techniques were used to extract the bit features. The artificial neural network black box was converted to white box in order to extract a mathematical equation and visibility of the model.
format Article
author Momeni, M.
Ridha, S.
Hosseiniz, S.J.
Liu, X.
Atashnezhad, A.
Ghaheri, S.
spellingShingle Momeni, M.
Ridha, S.
Hosseiniz, S.J.
Liu, X.
Atashnezhad, A.
Ghaheri, S.
Optimum drill bit selection by using bit images and mathematical investigation
author_sort Momeni, M.
title Optimum drill bit selection by using bit images and mathematical investigation
title_short Optimum drill bit selection by using bit images and mathematical investigation
title_full Optimum drill bit selection by using bit images and mathematical investigation
title_fullStr Optimum drill bit selection by using bit images and mathematical investigation
title_full_unstemmed Optimum drill bit selection by using bit images and mathematical investigation
title_sort optimum drill bit selection by using bit images and mathematical investigation
publisher Materials and Energy Research Center
publishDate 2017
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85036639979&doi=10.5829%2fije.2017.30.11b.24&partnerID=40&md5=6bc021c8c2756b8009f5686ec5f44413
http://eprints.utp.edu.my/19294/
_version_ 1741196183991222272
score 11.62408

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