Acoustic emission (AE) was recorded during tribological tests on 52,100 steel specimens under different loads. AE signals were transformed to the frequency domain using a Fast Fourier Transform and parameters such as power, RMS amplitude, mean frequency, and energy were analyzed and compared with friction coefficient and wear volume measurements. Results show that certain acoustic frequencies reflect friction while others reflect wear. If frequencies are chosen optimally, AE and friction signals are highly correlated (Pearson coefficients >0.8). SEM and Raman analysis reveal how plastic deformation and oxide formation affect friction, wear and AE simultaneously. AE recordings contains more information than conventional friction and wear volume measurements and are more sensitive to changes in mechanism. This all demonstrates AE's potential as a tool to monitor tribological behavior.