Vibration Parameters Identification of Rotating Blades Based on Blade Tip-Timing Sensor Waveforms
Source abstract
Abstract
Blade tip-timing is one of the most widely used non-contact measurement methods for rotating blade vibration. The classic blade tip-timing method is to identify the vibration parameters of the blade based on the time of blade tip arrival to the tip-timing sensor installed on the casing. Since the vibration measurement of blade tip-timing is a serious under-sampling method, the blade resonance frequency is usually higher than the sampling frequency of the BTT data acquisition system, resulting in a large identification error of blade vibration parameters. In view of the above shortcomings, a blade vibration parameters identification method is proposed based on the mapping matching between the static waveform of the sensor and the dynamic waveform of the blade tip-timing. The modulation effects of different vibration displacements, velocities and vibration amplitudes on the tip-timing waveform of the sensor are analyzed. The vibration displacements and velocities of the blade tip passing through the sensor are obtained by the waveform mapping method, and then the vibration parameters of the blade are identified. The influence of the number of blade tip-timing sensors on the identification accuracy of the blade vibration parameters identification algorithm is observed based on the waveform mapping theory. The identification accuracy of waveform mapping method is compared with other methods. The results show that compared with the under-sampled time of arrival (TOA) data of classic BTT applications, the modulation of the sensor waveform output by blade vibration can provide additional data, and the waveform mapping method can not only reduce the number of sensors but also improve the identification accuracy of blade vibration parameters. The waveform mapping method has higher identification accuracy of blade vibration parameters compared with the waveform method in the reference.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Bladed Disk Vibration Dynamics · Structural Health Monitoring Techniques · Vibration and Dynamic Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Mechanical Engineering and Automation, Liaoning University of Technology, Jinzhou 121001, China
Funding
National Natural Science Foundation of China · Liaoning Province Applied Basic Research Program Project · Key Laboratory of Vibration and Control of Aero-Propulsion System, Ministry of Education, Northeastern University · Liaoning Provincial Natural Science Foundation Guidance Program Project · Liaoning Provincial Department of Education Scientific Research General Project · Liaoning University of Technology Teacher Research Start Fund Project
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