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Sensor and Machine Condition Effects in Roller Bearing Diagnostics

Rolling element bearings are common components to almost all forms of rotating machinery. Bearing failure is one of the foremost causes of breakdowns in such machinery. This unexpected failure can be catastrophic (e.g., a helicopter main rotor bearing) or result in costly downtime (e.g., a process plant machine).

Critical machines are therefore subjected to continuous vibration monitoring for bearing health trending, to warn of impending failure, and/or shut down a machine to prevent further damage.

Such vibration monitoring systems are often effective, but depend on the system and sensor array to be in exactly the same condition for all measurements. The purpose of this thesis was to investigate the effects on vibration and acoustic emission signal metrics due to changes in: sensor type, sensor location, load, and speed.

The experimental setup consisted of a tapered roller-bearing test stand supplied by the Timken company. Results show that the acoustic emission and accelerometer each respond differently to the experimental changes in load and sensor location. The effect on different signal processing techniques is also studied.

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