ELKHA : Jurnal Teknik Elektro
Vol. 12 No. 2 October 2020

Klasterisasi Kerusakan Bearing Motor Induksi 3 Fasa Menggunakan Metode Transformasi Wavelet Diskrit dan K-Medoids

Naufal, Eska Rizqi (Unknown)
Priyandoko, Gigih (Unknown)
Hunaini, Fachrudin (Unknown)



Article Info

Publish Date
11 Oct 2020

Abstract

The 3 phase induction motor is a reliable and strong motor also has cheap price. However induction motor are also vulnerable, from the result of survey conducted by Electric Power Research Institute (EPRI), there are 41% cases of damage occur in the bearing caused by working environment condition, bearing age, and several other factors. Bearing fault is not easily to identified, with applying the data extraction method using the Discrete Wavelet Transform (DWT) and the K-Medoids clustering method will facilitate the identification process. The extraction method will pass the data in the form of current signals into the digital filter (Low Pass Filter and High Pass Filter) to be mapped into the region of frequency and time simultaneously, and clustering method will group data based on certain characteristics. Based on the clustering tests that have been done on the 3 phase induction motor current signal data with 3 bearing conditions, the Discrete Wavelet Transformation with mother wavelet bior1.1 decomposition level 2 and K-Medoids produce an accuracy rate of 86.8%.

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Journal Info

Abbrev

Elkha

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering

Description

The ELKHA publishes high-quality scientific journals related to Electrical and Computer Engineering and is associated with FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia / Indonesian Electrical Engineering Higher Education Forum). The scope of this journal covers the theory development, ...