Identification of gear mesh signals by kurtosis maximisation and its application to CH46 helicopter gearbox data

Author

Wang, Weverryi

Author_Institution

Aeronaut. & Maritime Res. Lab., Defence Sci. & Technol. Organ., Melbourne, Vic., Australia

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

369

Lastpage

372

Abstract

The detection and diagnosis of gearbox faults is of vital importance for the safe operation of helicopters. This paper presents a new approach in identifying gear mesh signals for early and effective detection of localised gear faults. Using this approach, the gear mesh signal is identified using a nonminimum phase autoregressive (AR) model by maximising the kurtosis of the inverse filter error signal of the model. Sudden changes in the error signal are usually indications of the existence of localised gear faults in the monitored gear. It is demonstrated using the well-regarded CH46 helicopter aft transmission test data that the approach shows great promise for detecting faults in complex gearboxes

Keywords

aerospace computing; aircraft testing; autoregressive processes; fault location; filters; helicopters; identification; optimisation; signal detection; CH46 helicopter; aft transmission test data; autoregressive model; fault diagnosis; gear mesh signal identification; gearbox fault detection; helicopters; inverse filter error signal; kurtosis maximisation; localised gear faults; nonminimum phase AR model; Data mining; Fault detection; Fault diagnosis; Filters; Gears; Helicopters; Shafts; Signal processing; Teeth; Vibration measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on

Print_ISBN

0-7803-7011-2

Type

conf

DOI

10.1109/SSP.2001.955299

Filename

955299