Fault diagnosis system of rotating machines using Hidden Markov Model (HMM)

Abstract

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.