Development of Effective and Efficient Fault Diagnostic Methodologies and Tools for Planetary Gearboxes
2017-10-22T00:00:00Z (GMT) by
Vibration analysis has been widely accepted in the field of machinery fault diagnosis. However, vibration signals theoretically have the amplitude modulation (AM) effect caused by time variant vibration transfer paths due to the rotation of planet carrier and sun gear. Their complex spectral structure makes it difficult to diagnose PGB faults via vibration analysis. In this dissertation, new effective and efficient PGB diagnostic methodologies and tools using alternative sensorshave been developed and validated with seeded fault tests with a PGB on a wind turbine simulator. Specifically, the following new effective and efficient PGB fault diagnostic methods are presented: a vibration based PGB diagnostic method, an acoustic emission (AE) based PGB diagnostic method, and a piezoelectric (PE) strain sensor based PGB diagnostic method. The newly developed PGB fault diagnostic methods and tools have several significant advantages. First, a new vibration based PGB fault diagnostic method was developed using the Welch’s spectral averaging. All localized PGB faults were isolable with this method while the conventional vibratory analyses of the time synchronous averaging (TSA), enveloping or the vibration separation (VS) techniques were not able to. Second, the heterodyning data acquisition (DAQ) system was applied to PGB in order to overcome the known challenge of the high sampling rate for AE analysis. Besides, with the AE based PGB fault diagnostic methods, not only it was isolating the location of the localized faults, but it is potentially capable of capturing incipient faults by using AE. Lastly, research reported in the literature has shown that strain sensor signals are closely related to torsional vibration, in which the only modulation effects are the AM and frequency modulation (FM) caused by gear faultsunder constant input and output torque. Also, results from the PE strain sensor based condition indicators (CIs) were isolable for all localized faults and remain relatively stationary within the same loading condition regardless the change of the shaft speed. Those CIs could be utilized in establishing a threshold based condition monitoring system and is verifying that the measurements from a PE strain sensor are heavily affected by the torque change.