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Nor Amadi, Dwi
JURNAL AGRI-TEK
Agriculture, Biological Sciences & Forestry

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Penerapan Metode Suport Vector Machine (Svm) Untuk Diagnosis Kerusakan Pada Bantalan Gelinding Nor Amadi, Dwi
JURNAL AGRI-TEK Vol 16, No 1 (2015): JURNAL AGRI-TEK
Publisher : JURNAL AGRI-TEK

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Abstract

Rolling element bearing fault on industrial machine can cause a serious problem in that industry because the whole production process willshuting down in a fiew times or days. That condition can cause a big losses on that company. Therefore, in this study the researchers will implement the support vector machine method to build an intelligent system for diagnosing rolling element bearing fault. so the rolling element bearing can be repaired or replaced before total damage occurs. The benefit are the company can minimize the losses caused by rolling element bearing fault.The vibration data from the Rolling element bearing will be extracted by using feature extraction to define a mapping the data from the original representation space into a new space where the classes are more easily separable and then the data will be processed with support vector machine method. After that, we can analyze the result to diagnose the rolling element bearing condition.Keywords : Intelligent System, Rolling Element Bearing Fault, SVM.
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