Shaft diagnostics and prognostics development and evaluation using damaged dynamic simulation

Abstract

This paper presents a shaft damage dynamic simulation methodology for development and evaluation of effective diagnostic and prognostic algorithms. The methodology uses dynamic shaft vibration models to simulate vibration signals with arbitrary shaft and operating conditions. These simulated vibration signals are used to develop and validate different diagnostic and prognostic algorithms. A simulation study to demonstrate the application of the methodology is provided. In comparison with traditional methods that acquire data from test rig or operational machines, the presented methodology has the following three major benefits. (1) It is able to simulate signals under any shaft and operating conditions (crack size, speed, torque), which is important because of the cost and time required to gather comprehensive operational and test bench data for algorithm development and validation. (2) The methodology could capture nuance for tiny faults without the contamination of extraneous variables, such as ambient noise, test stand dynamics, etc., that are not present in the actual case. Accuracy in this regard is crucial when using vibration data to diagnose faults, for instance to distinguish the effect of noise from a minor crack. (3) It may approach the true signatures of naturally occurring and growing faults more closely by comparison with artificially seeded fault tests or highly accelerated fatigue tests.