Galling detection by acoustic emission (AE) according to ASTM G98

Walaszek, Henri; Centre Technique des Industries Mecaniques; France

Hervé, C.; CETIM; France
Walaszek, H.; CETIM; France

ID: ECNDT-0346-2018
Session: Acoustic Emission 1
Room: J1
Date: 2018-06-13
Time: 15:40 - 16:00

For many mechanical companies, galling detection remains an important issue because it can occur in many mechanisms (bearings, transmissions…) and thus lead to serious failures. The diagnosis and identification of galling are made through facies observations and profilometry analysis. When contact surfaces are not visible or easily accessible, it is not possible to currently know the state of galling. It is therefore important to have a method capable of performing a reliable diagnosis without having to stop or disassemble considered machines. Acoustic emission is a monitoring method for detecting the start of this physical phenomenon between two surfaces and also to follow its evolution.
A feasibility study has been launched for ITER Org in order to demonstrate the capability of AE for the monitoring of galling in specific assemblies .Tests performed with CETIM tribology team have proved the potential of this method and also assess possibilities to develop a detection criteria based on acoustic emission features. The experimental principle is based on the ASTM G 98 by applying a load on a pin which is slowly rotated one revolution 360° relative to a fixed plate. The galling threshold is determined for each couple of material tested from the pressure at which there is a first material transfer on friction surfaces.
Thereafter further tests on other different couples of material have been performed and analysed with the following objectives:

-Detect galling from AE data using different post treatment strategies like correlation analysis, supervised and unsupervised pattern recognition, waveforms and frequency analysis
– Determine criteria associated to galling phenomenon beginning. Thanks to these criteria, an alarm is generated to prevent failure and send information to the maintenance operator when galling is detected.
– Quantify the galling severity. Different states of galling can be determined using pertinent AE features.