Date of Award


Document Type


First Advisor

Sundaresan, Mannur J.


Machine parts that are in relative motion often face a state of friction in their applications. The friction, when it is uncontrolled, can cause the machine part surfaces to degrade severely. At the time of service of a machine, relative motion between surfaces sometimes can cause crack growth of fretting fatigue. Conventional methods for determining the degree of deterioration and potential crack growth formation in in-situ application have not been proven sufficiently effective. Acoustic emission (AE) based Structural Health Monitoring (SHM) has the potential for real-time detection of damage growth in structures. But in the case of sliding contact between two surfaces, the relative motion encounters extraneous noise. In this research, two parallel bonded PZT sensors were used for detecting AE signals from sliding contacts. The time interval technique was taken into consideration to determine the authenticity of the hit source location, which reduced the noise data. Different parameters such as sliding velocities, normal pressure, and surface roughness were considered to determine their corresponding effect on AE signals. The nature of the waveforms in terms of frequency components present in the signal is also discussed. In this study, a surface profilometer was used to measure the change of roughness due to friction. Optical microscope images were taken to understand wear mechanisms involved in the wear of the friction surfaces. The dependence of the parameters on AE signals found in this research can be an effective tool for monitoring the early stages of wear in sliding contact.