SIMPLE EXPERT VISION SYSTEM FOR RECOGNITION OF BEARING'S DEFECTS

Authors

  • Agustian K. Herdianta
  • Aulia M.T. Nasution

DOI:

https://doi.org/10.21609/jiki.v5i2.188

Keywords:

backpropagation, bearing, kecacatan visual, visual defect

Abstract

Defects on a bearing is usually determined by observing its vibration characteristics. This method unfortunately can not detect the visual defects on the inner and outer ring bearing surface. A pattern recognition is implemented in this paper to solve the problem. A backpropagation neural network architecture is used to recognize the visual defect pattern. This architecture is integrated in a digital image processing chain. Recognition rate of good bearing is obtained at 92.93 %, meanwhile for defected bearing is obtained at 75 % respectively. This rate shows integrated artificial neural network with digital image processing can be implemented to detect the presence of visual bearing defect. Cacat pada bearing biasanya ditentukan dengan mengamati karakteristik getaran. Metode ini sayangnya tidak dapat mendeteksi kecacatan visual pada permukaan dalam dan luar cincin bearing. Sebuah pengenalan pola diimplementasikan dalam paper ini untuk memecahkan masalah tersebut. Sebuah arsitektur jaringan saraf backpropagation digunakan untuk mengenali pola kecacatan visual. Arsitektur yang diusulkan ini terintegrasi dalam sebuah alir pengolahan citra digital. Tingkat pengenalan bearing yang baik adalah 92.93%, sedangkan untuk bantalan yang cacat adalah 75%. Angka ini menunjukkan integrasi jaringan syaraf tiruan dengan pengolahan citra digital dapat diterapkan untuk mendeteksi kecacatan visual pada bearing.

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Published

2012-07-29

How to Cite

K. Herdianta, A., & Nasution, A. M. (2012). SIMPLE EXPERT VISION SYSTEM FOR RECOGNITION OF BEARING’S DEFECTS. Jurnal Ilmu Komputer Dan Informasi, 5(2), 57–62. https://doi.org/10.21609/jiki.v5i2.188

Issue

Vol. 5 No. 2 (2012): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)

Section

Articles

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