Deteksi Kerusakan Bearing Motor Induksi Dengan Analisa Arus Starting Menggunakan Transformasi Wavelet Diskrit Dan Jaringan Saraf Tiruan

Navasari, Eva (2018) Deteksi Kerusakan Bearing Motor Induksi Dengan Analisa Arus Starting Menggunakan Transformasi Wavelet Diskrit Dan Jaringan Saraf Tiruan. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kerusakan bearing pada motor induksi merupakan salah satu gangguan yang sering terjadi. Jenis kerusakan bearing itu sendiri terdiri dari kerusakan inner race, outer race dan bola bearing. Terjadinya kerusakan bearing ini dapat menyebabkan peningkatan vibrasi, kenaikan temperatur dan dapat menyebabkan kerusakan pada shaft, rotor dan stator. Untuk mempercepat proses perbaikan, deteksi kerusakan bearing harus bisa diklasifikasikan berdasarkan jenis kerusakan yang terjadi. Pada penelitian ini, kerusakan bearing akan dideteksi dengan analisa arus transien menggunakan metode transformasi wavelet diskrit. Untuk mengetahui terjadinya kerusakan, transformasi wavelet diskrit mengolah sinyal arus transien dengan membandingkan sub-band frekuensi sinyal pada saat bearing normal dan saat terjadi gangguan. Selanjutnya, jaringan saraf tiruan digunakan untuk memberikan informasi pengklasifikasian jenis kerusakan. Dengan klasifikasi kerusakan pada bearing ini, diharapkan dapat mempermudah dan mempercepat proses perbaikan.=========================================================================== Bearing damage in induction motor is one of the most common disruptions. The type of bearing damage itself consists of damage to the inner race, outer race and ball bearing. The occurrence of this bearing damage may cause increased vibration, temperature rise and may cause damage to the shafts, rotor and stator. To speed up the repair process, bearing damage detection should be classified according to the type of damage occurring. In this study, bearing damage will be detected by transient current analysis using discrete wavelet transform method. To determine the occurrence of damage, processing of transient current signals in discrete wavelet transforms is by comparing the signal frequency sub-band at normal bearings and during interruption. Furthermore, artificial neural networks are used to provide information on classification of types of damage. With the classification of damage to this bearing, it is expected to simplify and speed up the repair process.

Item Type: Thesis (Masters)
Additional Information: RTE 621.822 Nav d
Uncontrolled Keywords: Analysis of starting current, Bearing, Artificial Neural Network, Induction motor, Discrete wavelet transform
Subjects: Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science)
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2785 Electric motors, Induction.
Divisions: Faculty of Electrical Technology > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User: Eva Navasari
Date Deposited: 27 Nov 2020 07:37
Last Modified: 27 Nov 2020 07:37
URI: https://repository.its.ac.id/id/eprint/59009

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