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Non-Destructive Testing 92C. Hallai and P. Kulcsar (Editors)

© 1992 Elsevier Science Publishers B.V. All rights reserved.

Acoustic EiDiasion Monitoring of Aircra:f't Noises during a Ground Test

Gulahan Ra1 and C.R.L. Murthy

Department of Aerospace Engineering, Indian Institute of Science,Bangalore-560 012, India.

AbstractIn-flight monitoring of critical aircra1't components has been a long

felt need. And, acoustic emission is the most suitable candidate forthis purl)QSe. However, certain basic problems prevent directutilization of the tecllnique in its current state and preforce furtherinvestigations. The most important of these is the identification oftrue AE activity due to nucleation and growth of cracks in the presenceof various noise sources which camaflouge the signals. The workpresented in this paper deals with the attempts made to record noisesgenerated during an aircra:f't ground run as also a lab test.

1. INTRODUCTION

Investigations to develop AE for inflight monitoring are beingcontinuously pursued at the Indian Institute of Science since 1985 [1­4]. Crack propagation in a metal produces acoustic energy over a largeband of frequencies. This produces a relatively large response in AEsensors, but all non-crack signals must be discriminated against. Non­crack signals are background noises which include: Aircraft vibrations,Fretting noise from fasteners, Airflow noise, Hydraulic system noise,structural flexural noise, Jet noise Landing Gear operation noise andelectromagentic interference (:EM!~ from aircraft electrical andelectronic systems. Thus, in this paper, we present the attempts madeto record noises generated during an aircraft ground run, and alsounderstand and recognise the pattern of each one of them.

For the purpose of simulating the noises, test setup as shown inFig.1 is utilized. Four major classes of noises namely, mechanical(fretting), hydnmlic, airflow and :EM! were simulated in the lab first.

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For this purpose, an engine mount was used as the test piece.Mechanical (fretting) noise was generated by putting a loose pin in anengine mount and loading the mount with the help of a Material TestSystem. HYdraulic noise was generated by placing a senso~ on theactuator part of the MTS, applying high hydraulic pressure to theactuator without the load being applied to the test specimen. With thesensor placed on the specimen, a jet of air (from an air bottle) wasblown over the specimen and the airflow noise was picked up. EMI noisewas picked up by switching 'on and 'off' the equipment using power fromthe same phase as the AE monitoring system.

3. GROUND RUN

It has been emphasised earlier that non-crack signals i.e, backgroundnoises must be discriminated against to effectively utilise the AEtechnique towards in-flight monitoring. In order to understand theirpattern, four major classes of noises were picked up during the groundrun on MIG-21 ML aircraft at Air Force Technical College, Jalahalli,Bangalore. This aircraft is a cantilever all-metal mid-wing monoplanewith a delta wing, a controlled stabiliser and a sweptback tail unit.The aircraft is powered by a single axial-flow turbo-jet aero-engine.

AET5000~i;~~---tNORTHSTAR

I IGT

OSC ILLOSCOPE

SENSORS

Figure 1. Test setup for ground run

During the ground run of the aircraft, four sensors were used of whichthe first was located at the wing root joint, the second at the engine

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mount (the thrust bolt), the third at the horizontal stabiliser and thefourth in the cockpit. The choice of the location is based on thefollowing facts. Wing root joint is very close to the engine-drivenhudraulic pumps and hence sensor 1 would pick up the hydraulic noiseduring the ground running of the aircraft. Also, the structuralvibrations coming at the wiIlt!~root of the aircraft would be picked up bythis sensor. Sensor 2 would pick up the structural vibrations of thefuselage during ground running, as there is no other source of hydraulicor mechanical noise closeby. When the horizontal stabilizer isdeflected up and down to dissipate the hydraulic pressure in the systemafter cutting off the engine, sensor 3 would pick up the mechanicalnoise. The location of the sensor being in close proximity to the jet­pipe, it also would pick up jet noise during normal ground running ofthe aircraft.. Sensor 4 placed in the cockpit would pick up the EMInoise. Four files were created to store the data. To understand thepatterns in the data collected during the ground run, two types of plotshave been obtained.

a) Mean parameters per event Vs. time for each sensor.b) Distribution of events by various parameters for each sensor.

These plots have been taken for five AE parameters: Ringdown Counts(RDC), Peak Amplitude (PA), Rise Time (RT), Event Duration (ED) andEnergy (EN).

4. IDSULTS AND DISCUSSION

The results obtained from the data and the two types of plots wereanalysed and compared between the lab test and the ground runconsidering the two plots mentioned above and the ranges of theparameters for each source.

Though the results obtained in the lab and ground run differconsiderably in certain cases; the values of different parameters show adefinite trend which are summarised in the following while the ranges ofvalues are shown in Table 1. For Mechanical Noise, the mean values ofRDC, PA and EN were comparable in the two tests, while other twoparameters were higher in magnitude in the lab test than in ground run.The distribution of events showed low RDC values for the two tests,whereas there is conafderabl,e difference in the ranges of parametersover which the events have oecured in the two tests.

In case of Hydraulic noise, the mean values of all the fiveparameters were different in two tests, but a close similarity was seenin the mean values of all the parameters in the two ground runs athigher engine RPM. The distribution of events had the same range ofrespective parameters in two ground runs, these ranges being wider inlab test than in ground run.

For EMI noise, the mean values of the parameters for a large numberof events and their ranges were quite different in the two tests. Thisis because in the lab test EMI noise was picked up by switching 'on' and

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'off' the electrical equipment using power from the same phase as the AEmonitoring system, whereas in case of ground run, AE monitoring systemused ground power supply and the »IT noise was that from aircraftelectrical circuitry.

Table 1Range of parameters for different sources

Mechanical Hydraulic »IT Airflow

LAB TE3TImc- 1-5 1-100 1-26 1-79

PA 76-82 67-77 42-93 61-84RT 1-2 88-89 1-13 1-9,89ED 1-4 1-100 1-c:K> 1-100EN 76-100 66-100 56-100 60-100

GROUND RUNI=IDC- 1-17 4-30 1-16 1-24

PA 41-71 59-70 41-79 55-96RT 1-45 1-75 1-37 1-92ED 1-100 21-89 1-67 1-100EN 44-96 72-89 41-92 53-100

In the case of Airflow noise, the mean values of all the parametersare different in the two tests. And, there was a close similarity inthe values of RDC, RT and ED. The ranges of all the parameters overwhich the events have occured are again different in the two tests.These differences are because in the lab test aerodynamic noise wasgenerated by blowing air past the sensor, whereas in the ground run thejet noise was picked up. As the results indicate that the patterns ofthe noises are not completely distinguishing by considering individualparameters, analysis of the data is underway utiliZing patternrecognition with each of the four parameters as a feature.

5. CONCLUSIONS

Experiments were carried out to understand the AE characteristics ofnoise sources in an aircraft ground run. In ad.dition, AE data wasrecorded and compared with typical noises simulated in the laboratory .The results of these experiments indicate that RDC appears to be a goodparameter to distinguish between the various noises. The number ofevents occuring at particular values of all the parameters and theirranges are generally more in lab test than in ground run. The ranges ofparameters over which the events have occured are generally wider in lab

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test than in ground run. Data analysis using pattern recognitionapproach is in progress.

6. ACKNOWLEDGmEmS

The work reported in this paper is carried out under the AeronauticsResearch and Developnent Board project No.551. Assistance rendered byMr. M.R. Boot and Mr. H.V. Ramakrishna in the ground run is gratefullyacknowledged •

1. S.C. Pathak, "Acoustic :Emission Studies for Detection and MonitoringIncipient Cracks in Simulated Aeroengine Mount under Fatigue", MEProject Report, I.I.Sc., Bangalore, Jan. (1985).

2. S.A. Carvalho, "Crack Growth Studies in a Simulated Aeroengine Mountfor Inflight Monitoring using AE Technique". ME Project Report1.1.Sc., Bangalore, Jan. (1986).

3. V.R. Dahake, "Identification of Pre-cursors in AE Data: An approachfor Incipient Failure Detection through Inflight Monitoring" • MEproject report, I.I.Sc., Bangalore, Jan. (1989).

4. C.R.L. Murthy, H. Nagesh and M.H. Boot, "AE Monitoring of FatigueCrack Growth in an Aeroengine Mount", Technical Report to AR&DB,1. 1.se., Bangalore, March (1990) •

5. M. Abdul Majeed, "Unsupervised Pattern Classification of AESignals", M.Sc. Thesis, 1.1.Sc., Bangalore, Feb. (1987).