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A multi-physical signal correlation analysis method is proposed to identify the different tribological properties of materials. The acoustic emission (AE), contact resistance, and frictional force behaviors during dry sliding between four metals, 45# carbon steel, YG12 carbide, 2A12 aluminum alloy, and H62 brass, have been studied. Both positive and negative correlations between the root mean square of the amplified AE (AE RMS) signal and the frictional coefficient have been found in the experiments. In addition, the AE RMS signal and the contact resistance changed with changing sliding speed and normal load in different ways. The different correlation behaviors have been attributed to diverse tribological states under different experimental conditions due to different material characteristics. The correlation analysis provides a new method of quantitatively identifying the tribological states and the AE sources during frictional interaction. The observed anomalous correlations between the AE signal and frictional coefficient should be properly considered according to the different material properties during industrial friction condition monitoring using AE technology.

A correlation analysis method for analyzing tribological states using acoustic emission, frictional coefficient, and contact resistance signals