Advanced signal processing tools for helicopters’ future Health and Usage Monitoring Systems (HUMS)

Alexandre Mauricio,David Mba,Konstantinos Gryllias,Wenyi Wang,Linghao Zhou,Mathew Greaves,S Pantelakis,C Charitidis

doi:10.1051/matecconf/201930401021

Abstract

Health and Usage Monitoring Systems (HUMS) have been developed in order to monitor the health condition of helicopter drivetrains, focusing towards early, accurate and on time fault detection with limited false alarms and missed detections. Among other systems, the Main GearBox (MGB) is the heart of the drivetrain, reducing the high input speed generated by the engines, in order to provide the appropriate torque to the main rotors and to other auxiliary systems. HUMS are mounted on helicopters aiming to enhance the operational reliability and to support maintenance decision making, in order to increase the flight safety keeping in the meanwhile the overall maintenance cost low. Currently used HUMS seems to have reached their limits and the need for improvement has been recently highlighted by the post-accident analysis of the helicopter LN-OJF, which crashed in Norway in 2016. The aim of this paper is the application and further extension of recently proposed advanced cyclostationary based signal processing tools for the accurate detection of faults in helicopter gearboxes. The methodologies are tested, evaluated and compared with state of the art methods on datasets captured during experimental tests under various operating conditions on helicopter gearboxes, including a Category A Super Puma SA330 main planetary gearbox.

Highlights

Health and Usage Monitoring Systems (HUMS) conduct helicopter health monitoring by extracting Health Indicators (HI) from acquired vibration data
When the integration is performed on a specific narrow band instead of the full band, only the signature with carriers inside the integrated band are kept in the spectrum, nominated as the Improved Envelope Spectrum (IES)
The key objective of this paper is to evaluate the performance of the IESFOgram and compare it with state of the art methods by applying it on real vibration data acquired from a Main GearBox (MGB) of a Super Puma under various levels of damage on the planet bearing, operating under different speed and load conditions

Summary

Introduction

Health and Usage Monitoring Systems (HUMS) conduct helicopter health monitoring by extracting Health Indicators (HI) from acquired vibration data. The last decade, the interest in the development and use of cyclostationary based tools, such as the Cyclic Spectral Correlation (CSC) and Cyclic Spectral Coherence (CSCoh) for condition monitoring, has been increased as they achieve high performance in revealing hidden periodicities in their bi-variable representations Direct analysis of these results is difficult to perform, unless the analyst has extensive prior experience. When the integration is performed on a specific narrow band instead of the full band, only the signature with carriers inside the integrated band are kept in the spectrum, nominated as the Improved Envelope Spectrum (IES) This method achieves robust results in extracting hidden modulations in the spectrum, and results in a classical Envelope Spectrum of easy analysis [4, 5]. The key objective of this paper is to evaluate the performance of the IESFOgram and compare it with state of the art methods by applying it on real vibration data acquired from a MGB of a Super Puma under various levels of damage on the planet bearing, operating under different speed and load conditions

Objectives

Methods

Results

Conclusion