FAULT DIAGNOSIS SYSTEM OF ROTATING MACHINES USING HIDDEN MARKOV MODEL (HMM)

被引：0

作者：

Aditiya, Nur Ashar ^{[1
]}

Dharmawan, Muhammad Rizky ^{[1
]}

Darojah, Zaqiatud ^{[1
]}

Sanggar, Raden D. ^{[1
]}

机构：

[1] Politekn Elekt Negeri Surabaya, Mech & Energy Dept, Jalan Raya ITS, Sukolilo, Surabaya, Indonesia

来源：

2017 INTERNATIONAL ELECTRONICS SYMPOSIUM ON KNOWLEDGE CREATION AND INTELLIGENT COMPUTING (IES-KCIC) | 2017年

关键词：

diagnostic; classification; hidden markov model;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In the industry, maintenance costs can be reduced by early detection and diagnosis. It can also improve the overall equipment efficiency of the machine system. To diagnose the problem is required a diagnosis system with a particular method. The Hidden Markov Model (HMM) method is used because it can determine the parameters that are hidden from the observable parameters. Then, The specified parameters can be used for further analysis. This study, an error diagnostic system was applied on a rotating machinery using the Hidden Markov Model (HMM) analysis based on error recognition. The expected results are improving efficiency of equipment, diagnose faults on industrial machinery so that the maintenance costs can be reduced.

引用

页码：177 / 181

页数：5

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