Efficient Generation of Engine Representative Tip Timing Data Based on a Reduced Order Model for Bladed Rotors

Abstract

In modern compressors the assessment of blade vibration levels as well as health monitoring of the components are fundamental tasks. Traditionally, this assessment is done by the application of strain gauges to some blades of the assembly. In contrast to strain gauges, blade tip timing (BTT) offers a contactless monitoring of all blades of a rotor and there is no need of a telemetry system. A major issue in the interpretation of BTT data is the heavily undersampled nature of the signal. Usually, newly developed BTT algorithms are tested with sample data created by simplified structural models neglecting many of the uncertainties and disturbing influences of real applications. This work focuses on the creation of simulated BTT datasets as close as possible to real case measurements. For this purpose a subset of nominal system modes (SNM) representation of a compressor rotor is utilized. This model is able to include a large number of features present in real measurements, such as mistuning, static blade deflections due to centrifugal loads, aerodynamic damping and multiple mode resonances. Additionally, manufacturing deviations of the blade geometry, probe positioning errors in the BTT system and noise in the time of arrivals (TOAs) are captured by the BTT simulation environment. The main advantage of the created data is the possibility to steadily increase the signal complexity. Starting with a “perfect” signal the simulation environment is able to add different uncertainties one after the other. This allows the assessment of the influence of different features occurring in real measurements on the performance and accuracy of the analysis algorithms. Finally, a comparison of simulated BTT data and real data acquired from a rig test is shown to validate the presented approach of BTT data generation.

An experimentally validated modal model simulator for the assessment of different Blade Tip Timing algorithms

“…The literature review in [24] confirms the lack of multiple modes simulators that are based on realistic FE models. The similarities and differences between the simulator in [24] and the present one are detailed in section 2.2.…”

“…A somewhat similar approach is used in the simulators presented in [20,21], where the BTT data are synthesised from actual measurements using the minimum number of probes. It is also noted that FE-based simulators used in previous works (Khayrton [22], Diamond [23]) were limited to single mode resonance [24].…”

“…The simulator presented in this paper was first employed (but not presented in detail) by the authors in 2018 [3] in order to evaluate new algorithms for detecting steady movements. In the same year, independent researchers [24] presented a simulator that was also based on FEderived system modes. The work in [24] focused on tuning the simulator output to engine data, rather than assessing BTT algorithms.…”

“…In the same year, independent researchers [24] presented a simulator that was also based on FEderived system modes. The work in [24] focused on tuning the simulator output to engine data, rather than assessing BTT algorithms. The literature review in [24] confirms the lack of multiple modes simulators that are based on realistic FE models.…”

“…The work in [24] focused on tuning the simulator output to engine data, rather than assessing BTT algorithms. The literature review in [24] confirms the lack of multiple modes simulators that are based on realistic FE models. The similarities and differences between the simulator in [24] and the present one are detailed in section 2.2.…”