Open AccessIntelligent System for Gearbox Fault Detection & Diagnosis Based on Vibration Analysis using Bayesian Networks
Author(s) -
Dedik Romahadi,
Hui Xiong,
Hadi Pranoto
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/694/1/012001
Subject(s) - vibration , bayesian network , fault (geology) , bayesian probability , computer science , fault detection and isolation , pattern recognition (psychology) , artificial intelligence , acoustics , physics , geology , seismology , actuator
Moving energy from one machine to another and functioning to reduce speed while increasing torque is the ability of the gearbox. Due to many components and the structure between the components is fairly complex, thus to be able to detect the initial damage, sophisticated methods is needed. Vibration analysis is a method that has been effective in detecting the initial damage that occurs in machine. But it takes time and costs are not small to implement. The purpose of this study is to create an intelligent system capable of detecting gearbox damage based on data obtained from vibration measurements. Merging of two methods of vibration analysis and Bayesian networks is done to be able to design the system with the expected results. A series of multistate nodes are applied to the network and a system review is performed. Results are given and compared with results provided by the manual analysis. The results indicate that the system is feasible and reasonable which can assist inidentifying gearbox damages. This study definitively answers the problem of how to design an expert system capable of replacing the work of an expert on vibration analysis services.