Analog signal processing to improve acoustic emissions sensing

Acoustic Emissions (AE) are stress waves produced by the sudden internal stress redistribution of material caused by changes in the internal structure of the material. Possible causes of these changes are crack initiation and growth, crack opening/closure, or pitting in monolithic materials (gear/bearing material). Whereas vibration can measure the effect of damage, AE is a direct measure of damage. Unfortunately, AE methodologies suffer from the need of high sample rates (4 to 10 Msps) and relatively immature algorithms for condition indictors (CI). This paper hypothesizes that the AE signature is the result of some forcing function (e.g. periodic motion in the case of rotating machinery). As such, by demodulating the AE signature, one can reconstruct the information carried by the AE signature and provide improved diagnostics. As most on-line condition monitoring systems are embedded system, analog signal processing techniques are proposed which reduce the effective sample rate needed to operate on the AE signal to those similarly found in traditional vibration processing systems. This hypothesis is tested on a split torque gearbox and results are presented.