Gear tooth fault detection by autoregressive modelling

Author

Nikhar, Neeta K. ; Patankar, Sanika S. ; Kulkarni, J.V.

Author_Institution

Dept. of Instrum. Eng., Vishwakarma Inst. of Technol., Pune, India

fYear

2013

fDate

4-6 July 2013

Firstpage

1

Lastpage

6

Abstract

Gears are important element in a variety of industrial applications. An unexpected failure of the gear may cause significant economic losses. For that reason, fault diagnosis in gears has been the subject of intensive research. Vibration signal analysis has been widely used in the fault detection of rotation machinery. This paper present a gear tooth fault diagnosis technique of Autoregressive (AR) modeling of vibration signals. AR model coefficient is been determined by Yule-Walker equation with Levision-Durbin recursive algorithm. The model order is an essential part and is calculated by Akaike Information Criteria. The vibration signal of normal and faulty gear is been modeled and frequency response of AR model of the faulty gear is been compared with the AR model of the normal gear. The changes in the frequency spectrum indicate the fault.

Keywords

autoregressive processes; condition monitoring; failure analysis; fault diagnosis; gears; mechanical engineering computing; recursive estimation; signal processing; vibrations; Akaike information criteria; Levision-Durbin recursive algorithm; Yule-Walker equation; autoregressive modelling; failure analysis; fault diagnosis; gear tooth fault detection; rotation machinery; vibration signal analysis; Analytical models; Autoregressive processes; DC motors; Frequency response; Gears; Mathematical model; Vibrations; autoregressive models; frequency response; gear mesh frequency; mechanical gears; vibration measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Computing, Communications and Networking Technologies (ICCCNT),2013 Fourth International Conference on

Conference_Location

Tiruchengode

Print_ISBN

978-1-4799-3925-1

Type

conf

DOI

10.1109/ICCCNT.2013.6726528

Filename

6726528