The accurate monitoring of blade vibration under operating conditions is essential in turbo-machinery testing. Blade tip timing (BTT) is a promising non-contact technique for the measurement of blade vibrations. However, the BTT sampling data are inherently under-sampled and contaminated with several measurement uncertainties. How to recover frequency spectra of blade vibrations though processing these under-sampled biased signals is a bottleneck problem. A novel method of BTT signal processing for alleviating measurement uncertainties in recovery of multi-mode blade vibration frequency spectrum is proposed in this paper. The method can be divided into four phases. First, a single measurement vector model is built by exploiting that the blade vibration signals are sparse in frequency spectra. Secondly, the uniqueness of the nonnegative sparse solution is studied to achieve the vibration frequency spectrum. Thirdly, typical sources of BTT measurement uncertainties are quantitatively analyzed. Finally, an improved vibration frequency spectra recovery method is proposed to get a guaranteed level of sparse solution when measurement results are biased. Simulations and experiments are performed to prove the feasibility of the proposed method. The most outstanding advantage is that this method can prevent the recovered multi-mode vibration spectra from being affected by BTT measurement uncertainties without increasing the probe number.
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http://dx.doi.org/10.3390/s17081745 | DOI Listing |
Sensors (Basel)
December 2024
Faculty of Mechanical Engineering and Robotics, AGH University of Krakow, 30-059, Krakow, Poland.
In this study, a predictive maintenance (PdM) system focused on feature selection for the detection and classification of simulated defects in wind turbine blades has been developed. Traditional PdM systems often rely on numerous, broadly chosen diagnostic indicators derived from vibration data, yet many of these features offer little added value and may even degrade model performance. General feature selection methods might not be suitable for PdM solutions, as information regarding observed faults is often misinterpreted or lost.
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January 2025
College of Artificial Intelligence and Automation, Hohai University, Nanjing, China.
Independent pitch control (IPC) is a crucial technology for enhancing the performance of wind turbines, optimizing the power output, and reducing the loads by managing each blade. This paper explores the primary vibration modes of semi-submersible wind turbines under wind-wave coupling. Given the effectiveness of pitch control in vibration suppression, this paper addresses the limitations of conventional collective pitch control (CPC) by designing an independent pitch control method based on an equivalent wind speed model (EWIPC).
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December 2024
School of Data Science and Technology, North University of China, Taiyuan 030051, China.
Blades are the core components of rotating machinery, and the blade vibration status directly impacts the working efficiency and safe operation of the equipment. The blade tip timing (BTT) technique provides a solution for blade vibration monitoring and is currently a prominent topic in research on blade vibration issues. Nevertheless, the non-stationary factors present in actual engineering applications introduce inaccuracies in the BTT technique, resulting in blade vibration measurement errors.
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December 2024
Department of Industrial Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy.
Turbomachinery engines face significant failure risks due to the combination of thermal loads and high-amplitude vibrations in turbine and compressor blades. Accurate stress distribution measurements are critical for enhancing the performance and safety of these systems. Blade tip timing (BTT) has emerged as an advanced alternative to traditional measurement methods, capturing blade dynamics by detecting deviations in blade tip arrival times through sensors mounted on the stator casing.
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December 2024
College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou, 325035, China.
As a critical component of aero-engines, the processing quality of the blade has a significant impact on the engine's overall performance and service life. First, from the perspective of double abrasive grains, two finite element models-simultaneous and sequential scratches-are established. The interaction between the two abrasive grains affects not only the polishing force and chip formation but also the surface morphology of the processed workpiece.
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